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nature–inspired algorithm</title> <meta name="description" content="Search results for: nature–inspired algorithm"> <meta name="keywords" content="nature–inspired algorithm"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="nature–inspired algorithm"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 8129</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: nature–inspired algorithm</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8129</span> Elimination of Low Order Harmonics in Multilevel Inverter Using Nature-Inspired Metaheuristic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Ould%20Cherchali">N. Ould Cherchali</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Tlem%C3%A7ani"> A. Tlemçani</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20S.%20Boucherit"> M. S. Boucherit</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Morsli"> A. Morsli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nature-inspired metaheuristic algorithms, particularly those founded on swarm intelligence, have attracted much attention over the past decade. Firefly algorithm has appeared in approximately seven years ago, its literature has enlarged considerably with different applications. It is inspired by the behavior of fireflies. The aim of this paper is the application of firefly algorithm for solving a nonlinear algebraic system. This resolution is needed to study the Selective Harmonic Eliminated Pulse Width Modulation strategy (SHEPWM) to eliminate the low order harmonics; results have been applied on multilevel inverters. The final results from simulations indicate the elimination of the low order harmonics as desired. Finally, experimental results are presented to confirm the simulation results and validate the efficaciousness of the proposed approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=firefly%20algorithm" title="firefly algorithm">firefly algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristic%20algorithm" title=" metaheuristic algorithm"> metaheuristic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=multilevel%20inverter" title=" multilevel inverter"> multilevel inverter</a>, <a href="https://publications.waset.org/abstracts/search?q=SHEPWM" title=" SHEPWM"> SHEPWM</a> </p> <a href="https://publications.waset.org/abstracts/108337/elimination-of-low-order-harmonics-in-multilevel-inverter-using-nature-inspired-metaheuristic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/108337.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">146</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8128</span> Digestion Optimization Algorithm: A Novel Bio-Inspired Intelligence for Global Optimization Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Akintayo%20E.%20Akinsunmade">Akintayo E. Akinsunmade</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The digestion optimization algorithm is a novel biological-inspired metaheuristic method for solving complex optimization problems. The algorithm development was inspired by studying the human digestive system. The algorithm mimics the process of food ingestion, breakdown, absorption, and elimination to eﬀectively and eﬃciently search for optimal solutions. This algorithm was tested for optimal solutions on seven diﬀerent types of optimization benchmark functions. The algorithm produced optimal solutions with standard errors, which were compared with the exact solution of the test functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bio-inspired%20algorithm" title="bio-inspired algorithm">bio-inspired algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=benchmark%20optimization%20functions" title=" benchmark optimization functions"> benchmark optimization functions</a>, <a href="https://publications.waset.org/abstracts/search?q=digestive%20system%20in%20human" title=" digestive system in human"> digestive system in human</a>, <a href="https://publications.waset.org/abstracts/search?q=algorithm%20development" title=" algorithm development"> algorithm development</a> </p> <a href="https://publications.waset.org/abstracts/194133/digestion-optimization-algorithm-a-novel-bio-inspired-intelligence-for-global-optimization-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194133.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">8</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8127</span> Improved Multi–Objective Firefly Algorithms to Find Optimal Golomb Ruler Sequences for Optimal Golomb Ruler Channel Allocation </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shonak%20Bansal">Shonak Bansal</a>, <a href="https://publications.waset.org/abstracts/search?q=Prince%20Jain"> Prince Jain</a>, <a href="https://publications.waset.org/abstracts/search?q=Arun%20Kumar%20Singh"> Arun Kumar Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Neena%20Gupta"> Neena Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=channel%20allocation" title="channel allocation">channel allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=conventional%20computing" title=" conventional computing"> conventional computing</a>, <a href="https://publications.waset.org/abstracts/search?q=four%E2%80%93wave%20mixing" title=" four–wave mixing"> four–wave mixing</a>, <a href="https://publications.waset.org/abstracts/search?q=nature%E2%80%93inspired%20algorithm" title=" nature–inspired algorithm"> nature–inspired algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20Golomb%20ruler" title=" optimal Golomb ruler"> optimal Golomb ruler</a>, <a href="https://publications.waset.org/abstracts/search?q=l%C3%A9vy%20flight%20distribution" title=" lévy flight distribution"> lévy flight distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=improved%20multi%E2%80%93objective%20firefly%20algorithms" title=" improved multi–objective firefly algorithms"> improved multi–objective firefly algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=Pareto%20optimal" title=" Pareto optimal"> Pareto optimal</a> </p> <a href="https://publications.waset.org/abstracts/46108/improved-multi-objective-firefly-algorithms-to-find-optimal-golomb-ruler-sequences-for-optimal-golomb-ruler-channel-allocation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46108.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8126</span> A New Tool for Global Optimization Problems: Cuttlefish Algorithm </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adel%20Sabry%20Eesa">Adel Sabry Eesa</a>, <a href="https://publications.waset.org/abstracts/search?q=Adnan%20Mohsin%20Abdulazeez%20Brifcani"> Adnan Mohsin Abdulazeez Brifcani</a>, <a href="https://publications.waset.org/abstracts/search?q=Zeynep%20Orman"> Zeynep Orman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a new meta-heuristic bio-inspired optimization algorithm which is called Cuttlefish Algorithm (CFA). The algorithm mimics the mechanism of color changing behavior of the cuttlefish to solve numerical global optimization problems. The colors and patterns of the cuttlefish are produced by reflected light from three different layers of cells. The proposed algorithm considers mainly two processes: reflection and visibility. Reflection process simulates light reflection mechanism used by these layers, while visibility process simulates visibility of matching patterns of the cuttlefish. To show the effectiveness of the algorithm, it is tested with some other popular bio-inspired optimization algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Bees Algorithm (BA) that have been previously proposed in the literature. Simulations and obtained results indicate that the proposed CFA is superior when compared with these algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cuttlefish%20Algorithm" title="Cuttlefish Algorithm">Cuttlefish Algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=bio-inspired%20algorithms" title=" bio-inspired algorithms"> bio-inspired algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20optimization%20problems" title=" global optimization problems"> global optimization problems</a> </p> <a href="https://publications.waset.org/abstracts/11956/a-new-tool-for-global-optimization-problems-cuttlefish-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11956.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">563</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8125</span> Solving a Micromouse Maze Using an Ant-Inspired Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rolando%20Barradas">Rolando Barradas</a>, <a href="https://publications.waset.org/abstracts/search?q=Salviano%20Soares"> Salviano Soares</a>, <a href="https://publications.waset.org/abstracts/search?q=Ant%C3%B3nio%20Valente"> António Valente</a>, <a href="https://publications.waset.org/abstracts/search?q=Jos%C3%A9%20Alberto%20Lencastre"> José Alberto Lencastre</a>, <a href="https://publications.waset.org/abstracts/search?q=Paulo%20Oliveira"> Paulo Oliveira</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This article reviews the Ant Colony Optimization, a nature-inspired algorithm, and its implementation in the Scratch/m-Block programming environment. The Ant Colony Optimization is a part of Swarm Intelligence-based algorithms and is a subset of biological-inspired algorithms. Starting with a problem in which one has a maze and needs to find its path to the center and return to the starting position. This is similar to an ant looking for a path to a food source and returning to its nest. Starting with the implementation of a simple wall follower simulator, the proposed solution uses a dynamic graphical interface that allows young students to observe the ants’ movement while the algorithm optimizes the routes to the maze’s center. Things like interface usability, Data structures, and the conversion of algorithmic language to Scratch syntax were some of the details addressed during this implementation. This gives young students an easier way to understand the computational concepts of sequences, loops, parallelism, data, events, and conditionals, as they are used through all the implemented algorithms. Future work includes the simulation results with real contest mazes and two different pheromone update methods and the comparison with the optimized results of the winners of each one of the editions of the contest. It will also include the creation of a Digital Twin relating the virtual simulator with a real micromouse in a full-size maze. The first test results show that the algorithm found the same optimized solutions that were found by the winners of each one of the editions of the Micromouse contest making this a good solution for maze pathfinding. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nature%20inspired%20algorithms" title="nature inspired algorithms">nature inspired algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=scratch" title=" scratch"> scratch</a>, <a href="https://publications.waset.org/abstracts/search?q=micromouse" title=" micromouse"> micromouse</a>, <a href="https://publications.waset.org/abstracts/search?q=problem-solving" title=" problem-solving"> problem-solving</a>, <a href="https://publications.waset.org/abstracts/search?q=computational%20thinking" title=" computational thinking"> computational thinking</a> </p> <a href="https://publications.waset.org/abstracts/152186/solving-a-micromouse-maze-using-an-ant-inspired-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152186.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">125</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8124</span> An Analysis of Uncoupled Designs in Chicken Egg</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pratap%20Sriram%20Sundar">Pratap Sriram Sundar</a>, <a href="https://publications.waset.org/abstracts/search?q=Chandan%20Chowdhury"> Chandan Chowdhury</a>, <a href="https://publications.waset.org/abstracts/search?q=Sagar%20Kamarthi"> Sagar Kamarthi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nature has perfected her designs over 3.5 billion years of evolution. Research fields such as biomimicry, biomimetics, bionics, bio-inspired computing, and nature-inspired designs have explored nature-made artifacts and systems to understand nature’s mechanisms and intelligence. Learning from nature, the researchers have generated sustainable designs and innovation in a variety of fields such as energy, architecture, agriculture, transportation, communication, and medicine. Axiomatic design offers a method to judge if a design is good. This paper analyzes design aspects of one of the nature’s amazing object: chicken egg. The functional requirements (FRs) of components of the object are tabulated and mapped on to nature-chosen design parameters (DPs). The ‘independence axiom’ of the axiomatic design methodology is applied to analyze couplings and to evaluate if eggs’ design is good (i.e., uncoupled design) or bad (i.e., coupled design). The analysis revealed that eggs design is a good design, i.e., uncoupled design. This approach can be applied to any nature’s artifacts to judge whether their design is a good or a bad. This methodology is valuable for biomimicry studies. This approach can also be a very useful teaching design consideration of biology and bio-inspired innovation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=uncoupled%20design" title="uncoupled design">uncoupled design</a>, <a href="https://publications.waset.org/abstracts/search?q=axiomatic%20design" title=" axiomatic design"> axiomatic design</a>, <a href="https://publications.waset.org/abstracts/search?q=nature%20design" title=" nature design"> nature design</a>, <a href="https://publications.waset.org/abstracts/search?q=design%20evaluation" title=" design evaluation"> design evaluation</a> </p> <a href="https://publications.waset.org/abstracts/129725/an-analysis-of-uncoupled-designs-in-chicken-egg" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/129725.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">173</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8123</span> Test Suite Optimization Using an Effective Meta-Heuristic BAT Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anuradha%20Chug">Anuradha Chug</a>, <a href="https://publications.waset.org/abstracts/search?q=Sunali%20Gandhi"> Sunali Gandhi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Regression Testing is a very expensive and time-consuming process carried out to ensure the validity of modified software. Due to the availability of insufficient resources to re-execute all the test cases in time constrained environment, efforts are going on to generate test data automatically without human efforts. Many search based techniques have been proposed to generate efficient, effective as well as optimized test data, so that the overall cost of the software testing can be minimized. The generated test data should be able to uncover all potential lapses that exist in the software or product. Inspired from the natural behavior of bat for searching her food sources, current study employed a meta-heuristic, search-based bat algorithm for optimizing the test data on the basis certain parameters without compromising their effectiveness. Mathematical functions are also applied that can effectively filter out the redundant test data. As many as 50 Java programs are used to check the effectiveness of proposed test data generation and it has been found that 86% saving in testing efforts can be achieved using bat algorithm while covering 100% of the software code for testing. Bat algorithm was found to be more efficient in terms of simplicity and flexibility when the results were compared with another nature inspired algorithms such as Firefly Algorithm (FA), Hill Climbing Algorithm (HC) and Ant Colony Optimization (ACO). The output of this study would be useful to testers as they can achieve 100% path coverage for testing with minimum number of test cases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=regression%20testing" title="regression testing">regression testing</a>, <a href="https://publications.waset.org/abstracts/search?q=test%20case%20selection" title=" test case selection"> test case selection</a>, <a href="https://publications.waset.org/abstracts/search?q=test%20case%20prioritization" title=" test case prioritization"> test case prioritization</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=bat%20algorithm" title=" bat algorithm"> bat algorithm</a> </p> <a href="https://publications.waset.org/abstracts/55510/test-suite-optimization-using-an-effective-meta-heuristic-bat-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55510.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">380</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8122</span> Curve Fitting by Cubic Bezier Curves Using Migrating Birds Optimization Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mitat%20Uysal">Mitat Uysal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A new met heuristic optimization algorithm called as Migrating Birds Optimization is used for curve fitting by rational cubic Bezier Curves. This requires solving a complicated multivariate optimization problem. In this study, the solution of this optimization problem is achieved by Migrating Birds Optimization algorithm that is a powerful met heuristic nature-inspired algorithm well appropriate for optimization. The results of this study show that the proposed method performs very well and being able to fit the data points to cubic Bezier Curves with a high degree of accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=algorithms" title="algorithms">algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=Bezier%20curves" title=" Bezier curves"> Bezier curves</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristic%20optimization" title=" heuristic optimization"> heuristic optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=migrating%20birds%20optimization" title=" migrating birds optimization"> migrating birds optimization</a> </p> <a href="https://publications.waset.org/abstracts/78026/curve-fitting-by-cubic-bezier-curves-using-migrating-birds-optimization-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78026.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">336</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8121</span> Using Greywolf Optimized Machine Learning Algorithms to Improve Accuracy for Predicting Hospital Readmission for Diabetes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vincent%20Liu">Vincent Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diabetes" title="diabetes">diabetes</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=30-day%20readmission" title=" 30-day readmission"> 30-day readmission</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristic" title=" metaheuristic"> metaheuristic</a> </p> <a href="https://publications.waset.org/abstracts/181586/using-greywolf-optimized-machine-learning-algorithms-to-improve-accuracy-for-predicting-hospital-readmission-for-diabetes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181586.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">61</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8120</span> Bio-Inspired Design Approach Analysis: A Case Study of Antoni Gaudi and Santiago Calatrava</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marzieh%20Imani">Marzieh Imani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <em>Antoni Gaudi</em> and <em>Santiago Calatrava</em> have reputation for designing bio-inspired creative and technical buildings. Even though they have followed different independent approaches towards design, the source of bio-inspiration seems to be common. Taking a closer look at their projects reveals that <em>Calatrava</em> has been influenced by <em>Gaudi</em> in terms of interpreting nature and applying natural principles into the design process. This research firstly discusses the dialogue between Biomimicry and architecture. This review also explores human/nature discourse during the history by focusing on how nature revealed itself to the fine arts. This is explained by introducing <em>naturalism</em> and r<em>omantic</em> style in architecture as the outcome of designers’ inclination towards nature. Reviewing the literature, theoretical background and practical illustration of nature have been included. The most dominant practical aspects of imitating nature are form and function. Nature has been reflected in architectural science resulted in shaping different architectural styles such as organic, green, sustainable, bionic, and biomorphic. By defining a set of common aspects of Gaudi and <em>Calatrava</em>‘s design approach and by considering biomimetic design categories (organism, ecosystem, and behaviour as the main division and form, function, process, material, and construction as subdivisions), <em>Gaudi’s</em> and <em>Calatrava</em>’s project have been analysed. This analysis explores if their design approaches are equivalent or different. Based on this analysis, <em>Gaudi</em>’s architecture can be recognised as <em>biomorphic</em> while <em>Calatrava</em>’s projects are literally biomimetic. Referring to these architects, this review suggests a new set of principles by which a bio-inspired project can be determined either biomorphic or biomimetic. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biomimicry" title="biomimicry">biomimicry</a>, <a href="https://publications.waset.org/abstracts/search?q=Calatrava" title=" Calatrava"> Calatrava</a>, <a href="https://publications.waset.org/abstracts/search?q=Gaudi" title=" Gaudi"> Gaudi</a>, <a href="https://publications.waset.org/abstracts/search?q=nature" title=" nature"> nature</a> </p> <a href="https://publications.waset.org/abstracts/74401/bio-inspired-design-approach-analysis-a-case-study-of-antoni-gaudi-and-santiago-calatrava" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/74401.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">288</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8119</span> Method of Visual Prosthesis Design Based on Biologically Inspired Design</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shen%20Jian">Shen Jian</a>, <a href="https://publications.waset.org/abstracts/search?q=Hu%20Jie"> Hu Jie</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhu%20Guo%20Niu"> Zhu Guo Niu</a>, <a href="https://publications.waset.org/abstracts/search?q=Peng%20Ying%20Hong"> Peng Ying Hong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There are two issues exited in the traditional visual prosthesis: lacking systematic method and the low level of humanization. To tackcle those obstacles, a visual prosthesis design method based on biologically inspired design is proposed. Firstly, a constrained FBS knowledge cell model is applied to construct the functional model of visual prosthesis in biological field. Then the clustering results of engineering domain are ob-tained with the use of the cross-domain knowledge cell clustering algorithm. Finally, a prototype system is designed to support the bio-logically inspired design where the conflict is digested by TRIZ and other tools, and the validity of the method is verified by the solution scheme <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=knowledge-based%20engineering" title="knowledge-based engineering">knowledge-based engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20prosthesis" title=" visual prosthesis"> visual prosthesis</a>, <a href="https://publications.waset.org/abstracts/search?q=biologically%20inspired%20design" title=" biologically inspired design"> biologically inspired design</a>, <a href="https://publications.waset.org/abstracts/search?q=biomedical%20engineering" title=" biomedical engineering"> biomedical engineering</a> </p> <a href="https://publications.waset.org/abstracts/87977/method-of-visual-prosthesis-design-based-on-biologically-inspired-design" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87977.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">192</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8118</span> An Algorithm to Depreciate the Energy Utilization Using a Bio-Inspired Method in Wireless Sensor Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Navdeep%20Singh%20Randhawa">Navdeep Singh Randhawa</a>, <a href="https://publications.waset.org/abstracts/search?q=Shally%20Sharma"> Shally Sharma </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless Sensor Network is an autonomous technology emanating in the current scenario at a fast pace. This technology faces a number of defiance’s and energy management is one of them, which has a huge impact on the network lifetime. To sustain energy the different types of routing protocols have been flourished. The classical routing protocols are no more compatible to perform in complicated environments. Hence, in the field of routing the intelligent algorithms based on nature systems is a turning point in Wireless Sensor Network. These nature-based algorithms are quite efficient to handle the challenges of the WSN as they are capable of achieving local and global best optimization solutions for the complex environments. So, the main attention of this paper is to develop a routing algorithm based on some swarm intelligent technique to enhance the performance of Wireless Sensor Network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wireless%20sensor%20network" title="wireless sensor network">wireless sensor network</a>, <a href="https://publications.waset.org/abstracts/search?q=routing" title=" routing"> routing</a>, <a href="https://publications.waset.org/abstracts/search?q=swarm%20intelligence" title=" swarm intelligence"> swarm intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=MPRSO" title=" MPRSO"> MPRSO</a> </p> <a href="https://publications.waset.org/abstracts/57858/an-algorithm-to-depreciate-the-energy-utilization-using-a-bio-inspired-method-in-wireless-sensor-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57858.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">352</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8117</span> Multimodal Optimization of Density-Based Clustering Using Collective Animal Behavior Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kristian%20Bautista">Kristian Bautista</a>, <a href="https://publications.waset.org/abstracts/search?q=Ruben%20A.%20Idoy"> Ruben A. Idoy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A bio-inspired metaheuristic algorithm inspired by the theory of collective animal behavior (CAB) was integrated to density-based clustering modeled as multimodal optimization problem. The algorithm was tested on synthetic, Iris, Glass, Pima and Thyroid data sets in order to measure its effectiveness relative to CDE-based Clustering algorithm. Upon preliminary testing, it was found out that one of the parameter settings used was ineffective in performing clustering when applied to the algorithm prompting the researcher to do an investigation. It was revealed that fine tuning distance δ3 that determines the extent to which a given data point will be clustered helped improve the quality of cluster output. Even though the modification of distance δ3 significantly improved the solution quality and cluster output of the algorithm, results suggest that there is no difference between the population mean of the solutions obtained using the original and modified parameter setting for all data sets. This implies that using either the original or modified parameter setting will not have any effect towards obtaining the best global and local animal positions. Results also suggest that CDE-based clustering algorithm is better than CAB-density clustering algorithm for all data sets. Nevertheless, CAB-density clustering algorithm is still a good clustering algorithm because it has correctly identified the number of classes of some data sets more frequently in a thirty trial run with a much smaller standard deviation, a potential in clustering high dimensional data sets. Thus, the researcher recommends further investigation in the post-processing stage of the algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clustering" title="clustering">clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristics" title=" metaheuristics"> metaheuristics</a>, <a href="https://publications.waset.org/abstracts/search?q=collective%20animal%20behavior%20algorithm" title=" collective animal behavior algorithm"> collective animal behavior algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=density-based%20%20clustering" title=" density-based clustering"> density-based clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=multimodal%20optimization" title=" multimodal optimization"> multimodal optimization</a> </p> <a href="https://publications.waset.org/abstracts/94254/multimodal-optimization-of-density-based-clustering-using-collective-animal-behavior-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94254.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">230</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8116</span> Method of Cluster Based Cross-Domain Knowledge Acquisition for Biologically Inspired Design</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shen%20Jian">Shen Jian</a>, <a href="https://publications.waset.org/abstracts/search?q=Hu%20Jie"> Hu Jie</a>, <a href="https://publications.waset.org/abstracts/search?q=Ma%20Jin"> Ma Jin</a>, <a href="https://publications.waset.org/abstracts/search?q=Peng%20Ying%20Hong"> Peng Ying Hong</a>, <a href="https://publications.waset.org/abstracts/search?q=Fang%20Yi"> Fang Yi</a>, <a href="https://publications.waset.org/abstracts/search?q=Liu%20Wen%20Hai"> Liu Wen Hai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Biologically inspired design inspires inventions and new technologies in the field of engineering by mimicking functions, principles, and structures in the biological domain. To deal with the obstacles of cross-domain knowledge acquisition in the existing biologically inspired design process, functional semantic clustering based on functional feature semantic correlation and environmental constraint clustering composition based on environmental characteristic constraining adaptability are proposed. A knowledge cell clustering algorithm and the corresponding prototype system is developed. Finally, the effectiveness of the method is verified by the visual prosthetic device design. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=knowledge%20clustering" title="knowledge clustering">knowledge clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20acquisition" title=" knowledge acquisition"> knowledge acquisition</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20based%20engineering" title=" knowledge based engineering"> knowledge based engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20cell" title=" knowledge cell"> knowledge cell</a>, <a href="https://publications.waset.org/abstracts/search?q=biologically%20inspired%20design" title=" biologically inspired design"> biologically inspired design</a> </p> <a href="https://publications.waset.org/abstracts/70669/method-of-cluster-based-cross-domain-knowledge-acquisition-for-biologically-inspired-design" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70669.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">426</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8115</span> Elephant Herding Optimization for Service Selection in QoS-Aware Web Service Composition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samia%20Sadouki%20Chibani">Samia Sadouki Chibani</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelkamel%20Tari"> Abdelkamel Tari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Web service composition combines available services to provide new functionality. Given the number of available services with similar functionalities and different non functional aspects (QoS), the problem of finding a QoS-optimal web service composition is considered as an optimization problem belonging to NP-hard class. Thus, an optimal solution cannot be found by exact algorithms within a reasonable time. In this paper, a meta-heuristic bio-inspired is presented to address the QoS aware web service composition; it is based on Elephant Herding Optimization (EHO) algorithm, which is inspired by the herding behavior of elephant group. EHO is characterized by a process of dividing and combining the population to sub populations (clan); this process allows the exchange of information between local searches to move toward a global optimum. However, with Applying others evolutionary algorithms the problem of early stagnancy in a local optimum cannot be avoided. Compared with PSO, the results of experimental evaluation show that our proposition significantly outperforms the existing algorithm with better performance of the fitness value and a fast convergence. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bio-inspired%20algorithms" title="bio-inspired algorithms">bio-inspired algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=elephant%20herding%20optimization" title=" elephant herding optimization"> elephant herding optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=QoS%20optimization" title=" QoS optimization"> QoS optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=web%20service%20composition" title=" web service composition"> web service composition</a> </p> <a href="https://publications.waset.org/abstracts/64274/elephant-herding-optimization-for-service-selection-in-qos-aware-web-service-composition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64274.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">327</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8114</span> A Wireless Feedback Control System as a Base of Bio-Inspired Structure System to Mitigate Vibration in Structures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gwanghee%20Heo">Gwanghee Heo</a>, <a href="https://publications.waset.org/abstracts/search?q=Geonhyeok%20Bang"> Geonhyeok Bang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chunggil%20Kim"> Chunggil Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Chinok%20Lee"> Chinok Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper attempts to develop a wireless feedback control system as a primary step eventually toward a bio-inspired structure system where inanimate structure behaves like a life form autonomously. It is a standalone wireless control system which is supposed to measure externally caused structural responses, analyze structural state from acquired data, and take its own action on the basis of the analysis with an embedded logic. For an experimental examination of its effectiveness, we applied it on a model of two-span bridge and performed a wireless control test. Experimental tests have been conducted for comparison on both the wireless and the wired system under the conditions of Un-control, Passive-off, Passive-on, and Lyapunov control algorithm. By proving the congruence of the test result of the wireless feedback control system with the wired control system, its control performance was proven to be effective. Besides, it was found to be economical in energy consumption and also autonomous by means of a command algorithm embedded into it, which proves its basic capacity as a bio-inspired system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=structural%20vibration%20control" title="structural vibration control">structural vibration control</a>, <a href="https://publications.waset.org/abstracts/search?q=wireless%20system" title=" wireless system"> wireless system</a>, <a href="https://publications.waset.org/abstracts/search?q=MR%20damper" title=" MR damper"> MR damper</a>, <a href="https://publications.waset.org/abstracts/search?q=feedback%20control" title=" feedback control"> feedback control</a>, <a href="https://publications.waset.org/abstracts/search?q=embedded%20system" title=" embedded system"> embedded system</a> </p> <a href="https://publications.waset.org/abstracts/93059/a-wireless-feedback-control-system-as-a-base-of-bio-inspired-structure-system-to-mitigate-vibration-in-structures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93059.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">211</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8113</span> Continuous Differential Evolution Based Parameter Estimation Framework for Signal Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ammara%20Mehmood">Ammara Mehmood</a>, <a href="https://publications.waset.org/abstracts/search?q=Aneela%20Zameer"> Aneela Zameer</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Asif%20Zahoor%20Raja"> Muhammad Asif Zahoor Raja</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Faisal%20Fateh"> Muhammad Faisal Fateh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by deﬁning an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefﬁcient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=parameter%20estimation" title="parameter estimation">parameter estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=bio-inspired%20computing" title=" bio-inspired computing"> bio-inspired computing</a>, <a href="https://publications.waset.org/abstracts/search?q=continuous%20differential%20evolution%20%28CDE%29" title=" continuous differential evolution (CDE)"> continuous differential evolution (CDE)</a>, <a href="https://publications.waset.org/abstracts/search?q=periodic%20signals" title=" periodic signals"> periodic signals</a> </p> <a href="https://publications.waset.org/abstracts/72735/continuous-differential-evolution-based-parameter-estimation-framework-for-signal-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72735.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">302</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8112</span> Faulty Sensors Detection in Planar Array Antenna Using Pelican Optimization Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shafqat%20Ullah%20Khan">Shafqat Ullah Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ammar%20Nasir"> Ammar Nasir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Using planar antenna array (PAA) in radars, Broadcasting, satellite antennas, and sonar for the detection of targets, Helps provide instant beam pattern control. High flexibility and Adaptability are achieved by multiple beam steering by using a Planar array and are particularly needed in real-life Sanrio’s where the need arises for several high-directivity beams. Faulty sensors in planar arrays generate asymmetry, which leads to service degradation, radiation pattern distortion, and increased levels of sidelobe. The POA, a nature-inspired optimization algorithm, accurately determines faulty sensors within an array, enhancing the reliability and performance of planar array antennas through extensive simulations and experiments. The analysis was done for different types of faults in 7 x 7 and 8 x 8 planar arrays in MATLAB. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Planar%20antenna%20array" title="Planar antenna array">Planar antenna array</a>, <a href="https://publications.waset.org/abstracts/search?q=" title=""></a>, <a href="https://publications.waset.org/abstracts/search?q=Pelican%20optimisation%20Algorithm" title=" Pelican optimisation Algorithm"> Pelican optimisation Algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=" title=""></a>, <a href="https://publications.waset.org/abstracts/search?q=Faculty%20sensor" title=" Faculty sensor"> Faculty sensor</a>, <a href="https://publications.waset.org/abstracts/search?q=Antenna%20arrays" title=" Antenna arrays"> Antenna arrays</a> </p> <a href="https://publications.waset.org/abstracts/186381/faulty-sensors-detection-in-planar-array-antenna-using-pelican-optimization-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186381.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">79</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8111</span> Minimum Half Power Beam Width and Side Lobe Level Reduction of Linear Antenna Array Using Particle Swarm Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saeed%20Ur%20Rahman">Saeed Ur Rahman</a>, <a href="https://publications.waset.org/abstracts/search?q=Naveed%20Ullah"> Naveed Ullah</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Irshad%20Khan"> Muhammad Irshad Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=Quensheng%20Cao"> Quensheng Cao</a>, <a href="https://publications.waset.org/abstracts/search?q=Niaz%20Muhammad%20Khan"> Niaz Muhammad Khan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper the optimization performance of non-uniform linear antenna array is presented. The Particle Swarm Optimization (PSO) algorithm is presented to minimize Side Lobe Level (SLL) and Half Power Beamwidth (HPBW). The purpose of using the PSO algorithm is to get the optimum values for inter-element spacing and excitation amplitude of linear antenna array that provides a radiation pattern with minimum SLL and HPBW. Various design examples are considered and the obtain results using PSO are confirmed by comparing with results achieved using other nature inspired metaheuristic algorithms such as real coded genetic algorithm (RGA) and biogeography (BBO) algorithm. The comparative results show that optimization of linear antenna array using the PSO provides considerable enhancement in the SLL and HPBW. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=linear%20antenna%20array" title="linear antenna array">linear antenna array</a>, <a href="https://publications.waset.org/abstracts/search?q=minimum%20side%20lobe%20level" title=" minimum side lobe level"> minimum side lobe level</a>, <a href="https://publications.waset.org/abstracts/search?q=narrow%20half%20power%20beamwidth" title=" narrow half power beamwidth"> narrow half power beamwidth</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a> </p> <a href="https://publications.waset.org/abstracts/76942/minimum-half-power-beam-width-and-side-lobe-level-reduction-of-linear-antenna-array-using-particle-swarm-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/76942.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">552</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8110</span> Algorithms Inspired from Human Behavior Applied to Optimization of a Complex Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Curteanu">S. Curteanu</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Leon"> F. Leon</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Gavrilescu"> M. Gavrilescu</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20A.%20Floria"> S. A. Floria</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title="artificial neural networks">artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=human%20behaviors%20of%20learning%20and%20cooperation" title=" human behaviors of learning and cooperation"> human behaviors of learning and cooperation</a>, <a href="https://publications.waset.org/abstracts/search?q=human%20competitive%20behavior" title=" human competitive behavior"> human competitive behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20algorithms" title=" optimization algorithms"> optimization algorithms</a> </p> <a href="https://publications.waset.org/abstracts/149011/algorithms-inspired-from-human-behavior-applied-to-optimization-of-a-complex-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/149011.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">107</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8109</span> Energy Efficient Firefly Algorithm in Wireless Sensor Network </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wafa%E2%80%99%20Alsharafat">Wafa’ Alsharafat</a>, <a href="https://publications.waset.org/abstracts/search?q=Khalid%20Batiha"> Khalid Batiha</a>, <a href="https://publications.waset.org/abstracts/search?q=Alaa%20Kassab"> Alaa Kassab</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless sensor network (WSN) is comprised of a huge number of small and cheap devices known as sensor nodes. Usually, these sensor nodes are massively and deployed randomly as in Ad-hoc over hostile and harsh environment to sense, collect and transmit data to the needed locations (i.e., base station). One of the main advantages of WSN is that the ability to work in unattended and scattered environments regardless the presence of humans such as remote active volcanoes environments or earthquakes. In WSN expanding network, lifetime is a major concern. Clustering technique is more important to maximize network lifetime. Nature-inspired algorithms are developed and optimized to find optimized solutions for various optimization problems. We proposed Energy Efficient Firefly Algorithm to improve network lifetime as long as possible. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wireless%20network" title="wireless network">wireless network</a>, <a href="https://publications.waset.org/abstracts/search?q=SN" title=" SN"> SN</a>, <a href="https://publications.waset.org/abstracts/search?q=Firefly" title=" Firefly"> Firefly</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20efficiency" title=" energy efficiency "> energy efficiency </a> </p> <a href="https://publications.waset.org/abstracts/81257/energy-efficient-firefly-algorithm-in-wireless-sensor-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81257.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">389</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8108</span> A Bio-Inspired Approach to Produce Wettable Nylon Fabrics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sujani%20B.%20Y.%20Abeywardena">Sujani B. Y. Abeywardena</a>, <a href="https://publications.waset.org/abstracts/search?q=Srimala%20Perera"> Srimala Perera</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20M.%20Nalin%20De%20Silva"> K. M. Nalin De Silva</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Walpalage"> S. Walpalage</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Surface modifications are vital to accomplish the moisture management property in highly demanded synthetic fabrics. Biomimetic and bio-inspired surface modifications are identified as one of the fascinating areas of research. In this study, nature’s way of cooling elephants’ body temperature using mud bathing was mimicked to create a superior wettable nylon fabric with improved comfortability. For that, bentonite nanoclay was covalently grafted on nylon fabric using silane as a coupling agent. Fourier transform infrared spectra and Scanning electron microscopy images confirmed the successful grafting of nanoclay on nylon. The superior wettability of surface modified nylon was proved by standard protocols. This fabric coating strongly withstands more than 50 cycles of laundry. It is expected that this bio-inspired wettable nylon fabric may break the barrier of using nylon in various hydrophilic textile applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bentonite%20nanoclay" title="bentonite nanoclay">bentonite nanoclay</a>, <a href="https://publications.waset.org/abstracts/search?q=biomimetic" title=" biomimetic"> biomimetic</a>, <a href="https://publications.waset.org/abstracts/search?q=covalent%20modification" title=" covalent modification"> covalent modification</a>, <a href="https://publications.waset.org/abstracts/search?q=nylon%20fabric" title=" nylon fabric"> nylon fabric</a>, <a href="https://publications.waset.org/abstracts/search?q=surface" title=" surface"> surface</a>, <a href="https://publications.waset.org/abstracts/search?q=wettability" title=" wettability"> wettability</a> </p> <a href="https://publications.waset.org/abstracts/77249/a-bio-inspired-approach-to-produce-wettable-nylon-fabrics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77249.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">200</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8107</span> Spectrum Allocation in Cognitive Radio Using Monarch Butterfly Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Avantika%20Vats">Avantika Vats</a>, <a href="https://publications.waset.org/abstracts/search?q=Kushal%20Thakur"> Kushal Thakur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper displays the point at issue, improvement, and utilization of a Monarch Butterfly Optimization (MBO) rather than a Genetic Algorithm (GA) in cognitive radio for the channel portion. This approach offers a satisfactory approach to get the accessible range of both the users, i.e., primary users (PUs) and secondary users (SUs). The proposed enhancement procedure depends on a nature-inspired metaheuristic algorithm. In MBO, all the monarch butterfly individuals are located in two distinct lands, viz. Southern Canada and the northern USA (land 1), and Mexico (Land 2). The positions of the monarch butterflies are modernizing in two ways. At first, the offsprings are generated (position updating) by the migration operator and can be adjusted by the migration ratio. It is trailed by tuning the positions for different butterﬂies by the methods for the butterfly adjusting operator. To keep the population unaltered and minimize fitness evaluations, the aggregate of the recently produced butterﬂies in these two ways stays equivalent to the first population. The outcomes obviously display the capacity of the MBO technique towards ﬁnding the upgraded work values on issues regarding the genetic algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20radio" title="cognitive radio">cognitive radio</a>, <a href="https://publications.waset.org/abstracts/search?q=channel%20allocation" title=" channel allocation"> channel allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=monarch%20butterfly%20optimization" title=" monarch butterfly optimization"> monarch butterfly optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary" title=" evolutionary"> evolutionary</a>, <a href="https://publications.waset.org/abstracts/search?q=computation" title=" computation"> computation</a> </p> <a href="https://publications.waset.org/abstracts/181417/spectrum-allocation-in-cognitive-radio-using-monarch-butterfly-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181417.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">72</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8106</span> Adapting the Chemical Reaction Optimization Algorithm to the Printed Circuit Board Drilling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Taisir%20Eldos">Taisir Eldos</a>, <a href="https://publications.waset.org/abstracts/search?q=Aws%20Kanan"> Aws Kanan</a>, <a href="https://publications.waset.org/abstracts/search?q=Waleed%20Nazih"> Waleed Nazih</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Khatatbih"> Ahmad Khatatbih</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20algorithms" title="evolutionary algorithms">evolutionary algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=chemical%20reaction%20optimization" title=" chemical reaction optimization"> chemical reaction optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=traveling%20salesman" title=" traveling salesman"> traveling salesman</a>, <a href="https://publications.waset.org/abstracts/search?q=board%20drilling" title=" board drilling"> board drilling</a> </p> <a href="https://publications.waset.org/abstracts/20797/adapting-the-chemical-reaction-optimization-algorithm-to-the-printed-circuit-board-drilling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20797.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">519</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8105</span> Genetic Algorithm for Solving the Flexible Job-Shop Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Guilherme%20Baldo%20Carlos">Guilherme Baldo Carlos</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The flexible job-shop scheduling problem (FJSP) is an NP-hard combinatorial optimization problem, which can be applied to model several applications in a wide array of industries. This problem will have its importance increase due to the shift in the production mode that modern society is going through. The demands are increasing and for products personalized and customized. This work aims to apply a meta-heuristic called a genetic algorithm (GA) to solve this problem. A GA is a meta-heuristic inspired by the natural selection of Charles Darwin; it produces a population of individuals (solutions) and selects, mutates, and mates the individuals through generations in order to find a good solution for the problem. The results found indicate that the GA is suitable for FJSP solving. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title="genetic algorithm">genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20algorithm" title=" evolutionary algorithm"> evolutionary algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=flexible%20job-shop%20scheduling" title=" flexible job-shop scheduling"> flexible job-shop scheduling</a> </p> <a href="https://publications.waset.org/abstracts/132314/genetic-algorithm-for-solving-the-flexible-job-shop-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132314.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">147</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8104</span> System for the Detecting of Fake Profiles on Online Social Networks Using Machine Learning and the Bio-Inspired Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sekkal%20Nawel">Sekkal Nawel</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahammed%20Nadir"> Mahammed Nadir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The proliferation of online activities on Online Social Networks (OSNs) has captured significant user attention. However, this growth has been hindered by the emergence of fraudulent accounts that do not represent real individuals and violate privacy regulations within social network communities. Consequently, it is imperative to identify and remove these profiles to enhance the security of OSN users. In recent years, researchers have turned to machine learning (ML) to develop strategies and methods to tackle this issue. Numerous studies have been conducted in this field to compare various ML-based techniques. However, the existing literature still lacks a comprehensive examination, especially considering different OSN platforms. Additionally, the utilization of bio-inspired algorithms has been largely overlooked. Our study conducts an extensive comparison analysis of various fake profile detection techniques in online social networks. The results of our study indicate that supervised models, along with other machine learning techniques, as well as unsupervised models, are effective for detecting false profiles in social media. To achieve optimal results, we have incorporated six bio-inspired algorithms to enhance the performance of fake profile identification results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title="machine learning">machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=bio-inspired%20algorithm" title=" bio-inspired algorithm"> bio-inspired algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a>, <a href="https://publications.waset.org/abstracts/search?q=fake%20profile" title=" fake profile"> fake profile</a>, <a href="https://publications.waset.org/abstracts/search?q=system" title=" system"> system</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20network" title=" social network"> social network</a> </p> <a href="https://publications.waset.org/abstracts/174178/system-for-the-detecting-of-fake-profiles-on-online-social-networks-using-machine-learning-and-the-bio-inspired-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174178.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">67</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8103</span> Applications of Green Technology and Biomimicry in Civil Engineering with a Maglev Car Elevator</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sameer%20Ansari">Sameer Ansari</a>, <a href="https://publications.waset.org/abstracts/search?q=Suhas%20Nitsure"> Suhas Nitsure</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Biomimicry has made a big move into the built environment by adapting nature's solutions to human designs and inventions. We can examine numerous aspects of the built environment right from generating energy, fed by rainwater and powered by sun to over all land use impacts. This paper discusses the potential of a man made building which will work for the welfare of humans and reduce the impact of the harmful environment on us which we ourselves created for us. Building services inspired by nature such as building walls from homeostasis in organisms, natural ventilation from termites, artificial aggregates from natural aggregates, solar panels from photosynthesis and building structure itself compared to tree as a cantilever. Environmental services such as using CO2 as a feedstock for construction related activities, using Ornilux glasses and saving birds from collision with buildings, using prefabricated steel for fast building members- save time and also negligible waste as no formwork is used. Maglev inspired car elevators in building which is unique and giving all together new direction to technology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biomimicry" title="biomimicry">biomimicry</a>, <a href="https://publications.waset.org/abstracts/search?q=green%20technology" title=" green technology"> green technology</a>, <a href="https://publications.waset.org/abstracts/search?q=maglev%20car%20elevator" title=" maglev car elevator"> maglev car elevator</a>, <a href="https://publications.waset.org/abstracts/search?q=civil%20engineering" title=" civil engineering"> civil engineering</a> </p> <a href="https://publications.waset.org/abstracts/18416/applications-of-green-technology-and-biomimicry-in-civil-engineering-with-a-maglev-car-elevator" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18416.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">576</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8102</span> Artificial Reproduction System and Imbalanced Dataset: A Mendelian Classification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anita%20Kushwaha">Anita Kushwaha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bio-inspired%20computation" title="bio-inspired computation">bio-inspired computation</a>, <a href="https://publications.waset.org/abstracts/search?q=nature-%20inspired%20computation" title=" nature- inspired computation"> nature- inspired computation</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20computing" title=" natural computing"> natural computing</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a> </p> <a href="https://publications.waset.org/abstracts/54679/artificial-reproduction-system-and-imbalanced-dataset-a-mendelian-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54679.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">272</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8101</span> Optimal Energy Management and Environmental Index Optimization of a Microgrid Operating by Renewable and Sustainable Generation Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nabil%20Mezhoud">Nabil Mezhoud</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The economic operation of electric energy generating systems is one of the predominant problems in energy systems. Due to the need for better reliability, high energy quality, lower losses, lower cost and a clean environment, the application of renewable and sustainable energy sources, such as wind energy, solar energy, etc., in recent years has become more widespread. In this work, one of a bio-inspired meta-heuristic algorithm inspired by the flashing behavior of fireflies at night called the Firefly Algorithm (FFA) is applied to solve the Optimal Energy Management (OEM) and the environmental index (EI) problems of a micro-grid (MG) operating by Renewable and Sustainable Generation Systems (RSGS). Our main goal is to minimize the nonlinear objective function of an electrical microgrid, taking into account equality and inequality constraints. The FFA approach was examined and tested on a standard MG system composed of different types of RSGS, such as wind turbines (WT), photovoltaic systems (PV), and non-renewable energy, such as fuel cells (FC), micro turbine (MT), diesel generator (DEG) and loads with energy storage systems (ESS). The results are promising and show the effectiveness and robustness of the proposed approach to solve the OEM and the EI problems. The results of the proposed method have been compared and validated with those known references published recently. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=renewable%20energy%20sources" title="renewable energy sources">renewable energy sources</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20management" title=" energy management"> energy management</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20generator" title=" distributed generator"> distributed generator</a>, <a href="https://publications.waset.org/abstracts/search?q=micro-grids" title=" micro-grids"> micro-grids</a>, <a href="https://publications.waset.org/abstracts/search?q=firefly%20algorithm" title=" firefly algorithm"> firefly algorithm</a> </p> <a href="https://publications.waset.org/abstracts/177857/optimal-energy-management-and-environmental-index-optimization-of-a-microgrid-operating-by-renewable-and-sustainable-generation-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/177857.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">76</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8100</span> A Biologically Inspired Approach to Automatic Classification of Textile Fabric Prints Based On Both Texture and Colour Information</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Babar%20Khan">Babar Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=Wang%20Zhijie"> Wang Zhijie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Machine Vision has been playing a significant role in Industrial Automation, to imitate the wide variety of human functions, providing improved safety, reduced labour cost, the elimination of human error and/or subjective judgments, and the creation of timely statistical product data. Despite the intensive research, there have not been any attempts to classify fabric prints based on printed texture and colour, most of the researches so far encompasses only black and white or grey scale images. We proposed a biologically inspired processing architecture to classify fabrics w.r.t. the fabric print texture and colour. We created a texture descriptor based on the HMAX model for machine vision, and incorporated colour descriptor based on opponent colour channels simulating the single opponent and double opponent neuronal function of the brain. We found that our algorithm not only outperformed the original HMAX algorithm on classification of fabric print texture and colour, but we also achieved a recognition accuracy of 85-100% on different colour and different texture fabric. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automatic%20classification" title="automatic classification">automatic classification</a>, <a href="https://publications.waset.org/abstracts/search?q=texture%20descriptor" title=" texture descriptor"> texture descriptor</a>, <a href="https://publications.waset.org/abstracts/search?q=colour%20descriptor" title=" colour descriptor"> colour descriptor</a>, <a href="https://publications.waset.org/abstracts/search?q=opponent%20colour%20channel" title=" opponent colour channel"> opponent colour channel</a> </p> <a href="https://publications.waset.org/abstracts/31715/a-biologically-inspired-approach-to-automatic-classification-of-textile-fabric-prints-based-on-both-texture-and-colour-information" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31715.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">484</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=nature%E2%80%93inspired%20algorithm&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=nature%E2%80%93inspired%20algorithm&page=3">3</a></li> <li class="page-item"><a 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