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Search results for: ML algorithm
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for: ML algorithm</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3565</span> A Hybrid Distributed Algorithm for Multi-Objective Dynamic 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=Aydin%20Teymourifar">Aydin Teymourifar</a>, <a href="https://publications.waset.org/abstracts/search?q=Gurkan%20Ozturk"> Gurkan Ozturk</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a hybrid distributed algorithm has been suggested for multi-objective dynamic flexible job shop scheduling problem. The proposed algorithm is high level, in which several algorithms search the space on different machines simultaneously also it is a hybrid algorithm that takes advantages of the artificial intelligence, evolutionary and optimization methods. Distribution is done at different levels and new approaches are used for design of the algorithm. Apache spark and Hadoop frameworks have been used for the distribution of the algorithm. The Pareto optimality approach is used for solving the multi-objective benchmarks. The suggested algorithm that is able to solve large-size problems in short times has been compared with the successful algorithms of the literature. The results prove high speed and efficiency of the algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distributed%20algorithms" title="distributed algorithms">distributed algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=apache-spark" title=" apache-spark"> apache-spark</a>, <a href="https://publications.waset.org/abstracts/search?q=Hadoop" title=" Hadoop"> Hadoop</a>, <a href="https://publications.waset.org/abstracts/search?q=flexible%20dynamic%20job%20shop%20scheduling" title=" flexible dynamic job shop scheduling"> flexible dynamic job shop scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20optimization" title=" multi-objective optimization"> multi-objective optimization</a> </p> <a href="https://publications.waset.org/abstracts/72319/a-hybrid-distributed-algorithm-for-multi-objective-dynamic-flexible-job-shop-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72319.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">354</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">3564</span> A Variant of a Double Structure-Preserving QR Algorithm for Symmetric and Hamiltonian Matrices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Salam">Ahmed Salam</a>, <a href="https://publications.waset.org/abstracts/search?q=Haithem%20Benkahla"> Haithem Benkahla</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently, an efficient backward-stable algorithm for computing eigenvalues and vectors of a symmetric and Hamiltonian matrix has been proposed. The method preserves the symmetric and Hamiltonian structures of the original matrix, during the whole process. In this paper, we revisit the method. We derive a way for implementing the reduction of the matrix to the appropriate condensed form. Then, we construct a novel version of the implicit QR-algorithm for computing the eigenvalues and vectors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=block%20implicit%20QR%20algorithm" title="block implicit QR algorithm">block implicit QR algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=preservation%20of%20a%20double%20structure" title=" preservation of a double structure"> preservation of a double structure</a>, <a href="https://publications.waset.org/abstracts/search?q=QR%20algorithm" title=" QR algorithm"> QR algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=symmetric%20and%20Hamiltonian%20structures" title=" symmetric and Hamiltonian structures"> symmetric and Hamiltonian structures</a> </p> <a href="https://publications.waset.org/abstracts/61018/a-variant-of-a-double-structure-preserving-qr-algorithm-for-symmetric-and-hamiltonian-matrices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61018.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">409</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">3563</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">3562</span> Using Genetic Algorithms and Rough Set Based Fuzzy K-Modes to Improve Centroid Model Clustering Performance on Categorical Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rishabh%20Srivastav">Rishabh Srivastav</a>, <a href="https://publications.waset.org/abstracts/search?q=Divyam%20%20Sharma"> Divyam Sharma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose an algorithm to cluster categorical data named as ‘Genetic algorithm initialized rough set based fuzzy K-Modes for categorical data’. We propose an amalgamation of the simple K-modes algorithm, the Rough and Fuzzy set based K-modes and the Genetic Algorithm to form a new algorithm,which we hypothesise, will provide better Centroid Model clustering results, than existing standard algorithms. In the proposed algorithm, the initialization and updation of modes is done by the use of genetic algorithms while the membership values are calculated using the rough set and fuzzy logic. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=categorical%20data" title="categorical data">categorical data</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</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=K%20modes%20clustering" title=" K modes clustering"> K modes clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=rough%20sets" title=" rough sets"> rough sets</a> </p> <a href="https://publications.waset.org/abstracts/128558/using-genetic-algorithms-and-rough-set-based-fuzzy-k-modes-to-improve-centroid-model-clustering-performance-on-categorical-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/128558.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">246</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">3561</span> An Improved Ant Colony Algorithm for Genome Rearrangements</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Essam%20Al%20Daoud">Essam Al Daoud</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed permutation and evaluate the ants by using Kaplan algorithm. Two new operations are added to the standard ant colony algorithm: Replacing the worst ants by re-sampling the ants from a new probability distribution and applying the crossover operations on the best ants. The proposed algorithm is tested and compared with the improved breakpoint reversal sort algorithm by using three datasets. The results indicate that the proposed algorithm achieves better accuracy ratio than the previous methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ant%20colony%20algorithm" title="ant colony algorithm">ant colony algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=edit%20distance" title=" edit distance"> edit distance</a>, <a href="https://publications.waset.org/abstracts/search?q=genome%0D%0Abreakpoint" title=" genome breakpoint"> genome breakpoint</a>, <a href="https://publications.waset.org/abstracts/search?q=genome%20rearrangement" title=" genome rearrangement"> genome rearrangement</a>, <a href="https://publications.waset.org/abstracts/search?q=reversal%20sort" title=" reversal sort"> reversal sort</a> </p> <a href="https://publications.waset.org/abstracts/5601/an-improved-ant-colony-algorithm-for-genome-rearrangements" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5601.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">344</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">3560</span> Developing New Algorithm and Its Application on Optimal Control of Pumps in Water Distribution Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Rajabpour">R. Rajabpour</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Talebbeydokhti"> N. Talebbeydokhti</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20H.%20Ahmadi"> M. H. Ahmadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=G-JPSO" title="G-JPSO">G-JPSO</a>, <a href="https://publications.waset.org/abstracts/search?q=operation" title=" operation"> operation</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=pumping%20station" title=" pumping station"> pumping station</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20distribution%20networks" title=" water distribution networks"> water distribution networks</a> </p> <a href="https://publications.waset.org/abstracts/36259/developing-new-algorithm-and-its-application-on-optimal-control-of-pumps-in-water-distribution-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36259.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">401</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">3559</span> A Fast Silhouette Detection Algorithm for Shadow Volumes in Augmented Reality</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hoshang%20Kolivand">Hoshang Kolivand</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahyar%20Kolivand"> Mahyar Kolivand</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Shahrizal%20Sunar"> Mohd Shahrizal Sunar</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Azhar%20M.%20Arsad"> Mohd Azhar M. Arsad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Real-time shadow generation in virtual environments and Augmented Reality (AR) was always a hot topic in the last three decades. Lots of calculation for shadow generation among AR needs a fast algorithm to overcome this issue and to be capable of implementing in any real-time rendering. In this paper, a silhouette detection algorithm is presented to generate shadows for AR systems. Δ+ algorithm is presented based on extending edges of occluders to recognize which edges are silhouettes in the case of real-time rendering. An accurate comparison between the proposed algorithm and current algorithms in silhouette detection is done to show the reduction calculation by presented algorithm. The algorithm is tested in both virtual environments and AR systems. We think that this algorithm has the potential to be a fundamental algorithm for shadow generation in all complex environments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=silhouette%20detection" title="silhouette detection">silhouette detection</a>, <a href="https://publications.waset.org/abstracts/search?q=shadow%20volumes" title=" shadow volumes"> shadow volumes</a>, <a href="https://publications.waset.org/abstracts/search?q=real-time%20shadows" title=" real-time shadows"> real-time shadows</a>, <a href="https://publications.waset.org/abstracts/search?q=rendering" title=" rendering"> rendering</a>, <a href="https://publications.waset.org/abstracts/search?q=augmented%20reality" title=" augmented reality"> augmented reality</a> </p> <a href="https://publications.waset.org/abstracts/46127/a-fast-silhouette-detection-algorithm-for-shadow-volumes-in-augmented-reality" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46127.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">443</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">3558</span> An Enhanced Harmony Search (ENHS) Algorithm for Solving Optimization Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Talha%20A.%20Taj">Talha A. Taj</a>, <a href="https://publications.waset.org/abstracts/search?q=Talha%20A.%20Khan"> Talha A. Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Imran%20Khalid"> M. Imran Khalid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Optimization techniques attract researchers to formulate a problem and determine its optimum solution. This paper presents an Enhanced Harmony Search (ENHS) algorithm for solving optimization problems. The proposed algorithm increases the convergence and is more efficient than the standard Harmony Search (HS) algorithm. The paper discusses the novel techniques in detail and also provides the strategy for tuning the decisive parameters that affects the efficiency of the ENHS algorithm. The algorithm is tested on various benchmark functions, a real world optimization problem and a constrained objective function. Also, the results of ENHS are compared to standard HS, and various other optimization algorithms. The ENHS algorithms prove to be significantly better and more efficient than other algorithms. The simulation and testing of the algorithms is performed in MATLAB. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimization" title="optimization">optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=harmony%20search%20algorithm" title=" harmony search algorithm"> harmony search algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=MATLAB" title=" MATLAB"> MATLAB</a>, <a href="https://publications.waset.org/abstracts/search?q=electronic" title=" electronic"> electronic</a> </p> <a href="https://publications.waset.org/abstracts/3244/an-enhanced-harmony-search-enhs-algorithm-for-solving-optimization-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3244.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">463</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">3557</span> A Novel Algorithm for Production Scheduling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Mohammadi%20Bolban%20Abad">Ali Mohammadi Bolban Abad</a>, <a href="https://publications.waset.org/abstracts/search?q=Fariborz%20Ahmadi"> Fariborz Ahmadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Optimization in manufacture is a method to use limited resources to obtain the best performance and reduce waste. In this paper a new algorithm based on eurygaster life is introduced to obtain a plane in which task order and completion time of resources are defined. Evaluation results show our approach has less make span when the resources are allocated with some products in comparison to genetic algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20computation" title="evolutionary computation">evolutionary computation</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=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=NP-Hard%20problems" title=" NP-Hard problems"> NP-Hard problems</a>, <a href="https://publications.waset.org/abstracts/search?q=production%20scheduling" title=" production scheduling"> production scheduling</a> </p> <a href="https://publications.waset.org/abstracts/23914/a-novel-algorithm-for-production-scheduling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23914.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">378</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">3556</span> Downscaling Daily Temperature with Neuroevolutionary Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Min%20Shi">Min Shi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> State of the art research with Artificial Neural Networks for the downscaling of General Circulation Models (GCMs) mainly uses back-propagation algorithm as a training approach. This paper introduces another training approach of ANNs, Evolutionary Algorithm. The combined algorithm names neuroevolutionary (NE) algorithm. We investigate and evaluate the use of the NE algorithms in statistical downscaling by generating temperature estimates at interior points given information from a lattice of surrounding locations. The results of our experiments indicate that NE algorithms can be efficient alternative downscaling methods for daily temperatures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=temperature" title="temperature">temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=downscaling" title=" downscaling"> downscaling</a>, <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=evolutionary%20algorithms" title=" evolutionary algorithms"> evolutionary algorithms</a> </p> <a href="https://publications.waset.org/abstracts/29051/downscaling-daily-temperature-with-neuroevolutionary-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29051.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">349</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">3555</span> An Optimization Algorithm Based on Dynamic Schema with Dissimilarities and Similarities of Chromosomes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Radhwan%20Yousif%20Sedik%20Al-Jawadi">Radhwan Yousif Sedik Al-Jawadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Optimization is necessary for finding appropriate solutions to a range of real-life problems. In particular, genetic (or more generally, evolutionary) algorithms have proved very useful in solving many problems for which analytical solutions are not available. In this paper, we present an optimization algorithm called Dynamic Schema with Dissimilarity and Similarity of Chromosomes (DSDSC) which is a variant of the classical genetic algorithm. This approach constructs new chromosomes from a schema and pairs of existing ones by exploring their dissimilarities and similarities. To show the effectiveness of the algorithm, it is tested and compared with the classical GA, on 15 two-dimensional optimization problems taken from literature. We have found that, in most cases, our method is better than the classical genetic algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chromosome%20injection" title="chromosome injection">chromosome injection</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20schema" title=" dynamic schema"> dynamic schema</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=similarity%20and%20dissimilarity" title=" similarity and dissimilarity"> similarity and dissimilarity</a> </p> <a href="https://publications.waset.org/abstracts/54193/an-optimization-algorithm-based-on-dynamic-schema-with-dissimilarities-and-similarities-of-chromosomes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54193.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">346</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">3554</span> Simulation Approach for a Comparison of Linked Cluster Algorithm and Clusterhead Size Algorithm in Ad Hoc Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ameen%20Jameel%20Alawneh">Ameen Jameel Alawneh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A Mobile ad-hoc network (MANET) is a collection of wireless mobile hosts that dynamically form a temporary network without the aid of a system administrator. It has neither fixed infrastructure nor wireless ad hoc sessions. It inherently reaches several nodes with a single transmission, and each node functions as both a host and a router. The network maybe represented as a set of clusters each managed by clusterhead. The cluster size is not fixed and it depends on the movement of nodes. We proposed a clusterhead size algorithm (CHSize). This clustering algorithm can be used by several routing algorithms for ad hoc networks. An elected clusterhead is assigned for communication with all other clusters. Analysis and simulation of the algorithm has been implemented using GloMoSim networks simulator, MATLAB and MAPL11 proved that the proposed algorithm achieves the goals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=simulation" title="simulation">simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=MANET" title=" MANET"> MANET</a>, <a href="https://publications.waset.org/abstracts/search?q=Ad-hoc" title=" Ad-hoc"> Ad-hoc</a>, <a href="https://publications.waset.org/abstracts/search?q=cluster%20head%20size" title=" cluster head size"> cluster head size</a>, <a href="https://publications.waset.org/abstracts/search?q=linked%20cluster%20algorithm" title=" linked cluster algorithm"> linked cluster algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=loss%20and%20dropped%20packets" title=" loss and dropped packets"> loss and dropped packets</a> </p> <a href="https://publications.waset.org/abstracts/41610/simulation-approach-for-a-comparison-of-linked-cluster-algorithm-and-clusterhead-size-algorithm-in-ad-hoc-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41610.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">391</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">3553</span> Hybrid Algorithm for Frequency Channel Selection in Wi-Fi Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cesar%20Hern%C3%A1ndez">Cesar Hernández</a>, <a href="https://publications.waset.org/abstracts/search?q=Diego%20Giral"> Diego Giral</a>, <a href="https://publications.waset.org/abstracts/search?q=Ingrid%20P%C3%A1ez"> Ingrid Páez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics is used. These metrics are the accumulative average of failed handoffs, the accumulative average of handoffs performed, the accumulative average of transmission bandwidth, and the accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW 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=decision%20making" title=" decision making"> decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20algorithm" title=" hybrid algorithm"> hybrid algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=spectrum%20handoff" title=" spectrum handoff"> spectrum handoff</a>, <a href="https://publications.waset.org/abstracts/search?q=wireless%20networks" title=" wireless networks"> wireless networks</a> </p> <a href="https://publications.waset.org/abstracts/34830/hybrid-algorithm-for-frequency-channel-selection-in-wi-fi-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34830.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">541</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">3552</span> Modified Active (MA) Algorithm to Generate Semantic Web Related Clustered Hierarchy for Keyword Search</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20Leena%20Giri">G. Leena Giri</a>, <a href="https://publications.waset.org/abstracts/search?q=Archana%20Mathur"> Archana Mathur</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20H.%20Manjula"> S. H. Manjula</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20R.%20Venugopal"> K. R. Venugopal</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20M.%20Patnaik"> L. M. Patnaik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Keyword search in XML documents is based on the notion of lowest common ancestors in the labelled trees model of XML documents and has recently gained a lot of research interest in the database community. In this paper, we propose the Modified Active (MA) algorithm which is an improvement over the active clustering algorithm by taking into consideration the entity aspect of the nodes to find the level of the node pertaining to a particular keyword input by the user. A portion of the bibliography database is used to experimentally evaluate the modified active algorithm and results show that it performs better than the active algorithm. Our modification improves the response time of the system and thereby increases the efficiency of the system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=keyword%20matching%20patterns" title="keyword matching patterns">keyword matching patterns</a>, <a href="https://publications.waset.org/abstracts/search?q=MA%20algorithm" title=" MA algorithm"> MA algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20search" title=" semantic search"> semantic search</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20management" title=" knowledge management"> knowledge management</a> </p> <a href="https://publications.waset.org/abstracts/6608/modified-active-ma-algorithm-to-generate-semantic-web-related-clustered-hierarchy-for-keyword-search" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6608.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">413</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">3551</span> Cuckoo Search (CS) Optimization Algorithm for Solving Constrained Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sait%20Ali%20Uymaz">Sait Ali Uymaz</a>, <a href="https://publications.waset.org/abstracts/search?q=G%C3%BClay%20Tezel"> Gülay Tezel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the comparison results on the performance of the Cuckoo Search (CS) algorithm for constrained optimization problems. For constraint handling, CS algorithm uses penalty method. CS algorithm is tested on thirteen well-known test problems and the results obtained are compared to Particle Swarm Optimization (PSO) algorithm. Mean, best, median and worst values were employed for the analyses of performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cuckoo%20search" title="cuckoo search">cuckoo search</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=constrained%20optimization%20problems" title=" constrained optimization problems"> constrained optimization problems</a>, <a href="https://publications.waset.org/abstracts/search?q=penalty%20method" title=" penalty method"> penalty method</a> </p> <a href="https://publications.waset.org/abstracts/13991/cuckoo-search-cs-optimization-algorithm-for-solving-constrained-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13991.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">557</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">3550</span> Left to Right-Right Most Parsing Algorithm with Lookahead</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jamil%20Ahmed">Jamil Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Left to Right-Right Most (LR) parsing algorithm is a widely used algorithm of syntax analysis. It is contingent on a parsing table, whereas the parsing tables are extracted from the grammar. The parsing table specifies the actions to be taken during parsing. It requires that the parsing table should have no action conflicts for the same input symbol. This requirement imposes a condition on the class of grammars over which the LR algorithms work. However, there are grammars for which the parsing tables hold action conflicts. In such cases, the algorithm needs a capability of scanning (looking-ahead) next input symbols ahead of the current input symbol. In this paper, a ‘Left to Right’-‘Right Most’ parsing algorithm with lookahead capability is introduced. The 'look-ahead' capability in the LR parsing algorithm is the major contribution of this paper. The practicality of the proposed algorithm is substantiated by the parser implementation of the Context Free Grammar (CFG) of an already proposed programming language 'State Controlled Object Oriented Programming' (SCOOP). SCOOP’s Context Free Grammar has 125 productions and 192 item sets. This algorithm parses SCOOP while the grammar requires to ‘look ahead’ the input symbols due to action conflicts in its parsing table. Proposed LR parsing algorithm with lookahead capability can be viewed as an optimization of ‘Simple Left to Right’-‘Right Most’ (SLR) parsing algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=left%20to%20right-right%20most%20parsing" title="left to right-right most parsing">left to right-right most parsing</a>, <a href="https://publications.waset.org/abstracts/search?q=syntax%20analysis" title=" syntax analysis"> syntax analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=bottom-up%20parsing%20algorithm" title=" bottom-up parsing algorithm"> bottom-up parsing algorithm</a> </p> <a href="https://publications.waset.org/abstracts/128733/left-to-right-right-most-parsing-algorithm-with-lookahead" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/128733.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">126</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">3549</span> Improved Whale Algorithm Based on Information Entropy and Its Application in Truss Structure Optimization Design</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Serges%20Mendomo%20%20Meye">Serges Mendomo Meye</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Guowei"> Li Guowei</a>, <a href="https://publications.waset.org/abstracts/search?q=Shen%20Zhenzhong"> Shen Zhenzhong</a>, <a href="https://publications.waset.org/abstracts/search?q=Gan%20Lei"> Gan Lei</a>, <a href="https://publications.waset.org/abstracts/search?q=Xu%20Liqun"> Xu Liqun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Given the limitations of the original whale optimization algorithm (WAO) in local optimum and low convergence accuracy in truss structure optimization problems, based on the fundamental whale algorithm, an improved whale optimization algorithm (SWAO) based on information entropy is proposed. The information entropy itself is an uncertain measure. It is used to control the range of whale searches in path selection. It can overcome the shortcomings of the basic whale optimization algorithm (WAO) and can improve the global convergence speed of the algorithm. Taking truss structure as the optimization research object, the mathematical model of truss structure optimization is established; the cross-sectional area of truss is taken as the design variable; the objective function is the weight of truss structure; and an improved whale optimization algorithm (SWAO) is used for optimization design, which provides a new idea and means for its application in large and complex engineering structure optimization design. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=information%20entropy" title="information entropy">information entropy</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20optimization" title=" structural optimization"> structural optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=truss%20structure" title=" truss structure"> truss structure</a>, <a href="https://publications.waset.org/abstracts/search?q=whale%20algorithm" title=" whale algorithm"> whale algorithm</a> </p> <a href="https://publications.waset.org/abstracts/139986/improved-whale-algorithm-based-on-information-entropy-and-its-application-in-truss-structure-optimization-design" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/139986.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">249</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">3548</span> Parallel Version of Reinhard’s Color Transfer Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abhishek%20Bhardwaj">Abhishek Bhardwaj</a>, <a href="https://publications.waset.org/abstracts/search?q=Manish%20Kumar%20Bajpai"> Manish Kumar Bajpai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An image with its content and schema of colors presents an effective mode of information sharing and processing. By changing its color schema different visions and prospect are discovered by the users. This phenomenon of color transfer is being used by Social media and other channel of entertainment. Reinhard et al’s algorithm was the first one to solve this problem of color transfer. In this paper, we make this algorithm efficient by introducing domain parallelism among different processors. We also comment on the factors that affect the speedup of this problem. In the end by analyzing the experimental data we claim to propose a novel and efficient parallel Reinhard’s algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Reinhard%20et%20al%E2%80%99s%20algorithm" title="Reinhard et al’s algorithm">Reinhard et al’s algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=color%20transferring" title=" color transferring"> color transferring</a>, <a href="https://publications.waset.org/abstracts/search?q=parallelism" title=" parallelism"> parallelism</a>, <a href="https://publications.waset.org/abstracts/search?q=speedup" title=" speedup"> speedup</a> </p> <a href="https://publications.waset.org/abstracts/21874/parallel-version-of-reinhards-color-transfer-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21874.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">614</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">3547</span> A Filtering Algorithm for a Nonlinear State-Space Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20Eqal%20Al%20Mazrooei">Abdullah Eqal Al Mazrooei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Kalman filter is a famous algorithm that utilizes to estimate the state in the linear systems. It has numerous applications in technology and science. Since of the most of applications in real life can be described by nonlinear systems. So, Kalman filter does not work with the nonlinear systems because it is suitable to linear systems only. In this work, a nonlinear filtering algorithm is presented which is suitable to use with the special kinds of nonlinear systems. This filter generalizes the Kalman filter. This means that this filter also can be used for the linear systems. Our algorithm depends on a special linearization of the second degree. We introduced the nonlinear algorithm with a bilinear state-space model. A simulation example is presented to illustrate the efficiency of the algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title="Kalman filter">Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=filtering%20algorithm" title=" filtering algorithm"> filtering algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20systems" title=" nonlinear systems"> nonlinear systems</a>, <a href="https://publications.waset.org/abstracts/search?q=state-space%20model" title=" state-space model"> state-space model</a> </p> <a href="https://publications.waset.org/abstracts/74331/a-filtering-algorithm-for-a-nonlinear-state-space-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/74331.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">375</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">3546</span> Chemical Reaction Algorithm for Expectation Maximization Clustering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Li%20Ni">Li Ni</a>, <a href="https://publications.waset.org/abstracts/search?q=Pen%20ManMan"> Pen ManMan</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20KenLi"> Li KenLi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems. <p class="card-text"><strong>Keywords:</strong> <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=expection%20maimization" title=" expection maimization"> expection maimization</a>, <a href="https://publications.waset.org/abstracts/search?q=initia" title=" initia"> initia</a>, <a href="https://publications.waset.org/abstracts/search?q=objective%20function%20clustering" title=" objective function clustering"> objective function clustering</a> </p> <a href="https://publications.waset.org/abstracts/54706/chemical-reaction-algorithm-for-expectation-maximization-clustering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54706.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">713</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">3545</span> An Improved Genetic Algorithm for Traveling Salesman Problem with Precedence Constraint</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20F.%20F.%20Ab%20Rashid">M. F. F. Ab Rashid</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20N.%20Mohd%20Rose"> A. N. Mohd Rose</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20M.%20Z.%20Nik%20Mohamed"> N. M. Z. Nik Mohamed</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20S.%20Wan%20Harun"> W. S. Wan Harun</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20A.%20Che%20Ghani"> S. A. Che Ghani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traveling salesman problem with precedence constraint (TSPPC) is one of the most complex problems in combinatorial optimization. The existing algorithms to solve TSPPC cost large computational time to find the optimal solution. The purpose of this paper is to present an efficient genetic algorithm that guarantees optimal solution with less number of generations and iterations time. Unlike the existing algorithm that generates priority factor as chromosome, the proposed algorithm directly generates sequence of solution as chromosome. As a result, the proposed algorithm is capable of generating optimal solution with smaller number of generations and iteration time compare to existing algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=traveling%20salesman%20problem" title="traveling salesman problem">traveling salesman problem</a>, <a href="https://publications.waset.org/abstracts/search?q=sequencing" title=" sequencing"> sequencing</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=precedence%20constraint" title=" precedence constraint"> precedence constraint</a> </p> <a href="https://publications.waset.org/abstracts/15486/an-improved-genetic-algorithm-for-traveling-salesman-problem-with-precedence-constraint" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15486.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">560</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">3544</span> Improved FP-Growth Algorithm with Multiple Minimum Supports Using Maximum Constraints</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elsayeda%20M.%20Elgaml">Elsayeda M. Elgaml</a>, <a href="https://publications.waset.org/abstracts/search?q=Dina%20M.%20Ibrahim"> Dina M. Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Elsayed%20A.%20Sallam"> Elsayed A. Sallam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FP-growth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=association%20rules" title="association rules">association rules</a>, <a href="https://publications.waset.org/abstracts/search?q=FP-growth" title=" FP-growth"> FP-growth</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20minimum%20supports" title=" multiple minimum supports"> multiple minimum supports</a>, <a href="https://publications.waset.org/abstracts/search?q=Weka%20tool" title=" Weka tool"> Weka tool</a> </p> <a href="https://publications.waset.org/abstracts/28521/improved-fp-growth-algorithm-with-multiple-minimum-supports-using-maximum-constraints" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28521.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">485</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">3543</span> An Improved Many Worlds Quantum Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Li%20Dan">Li Dan</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhao%20Junsuo"> Zhao Junsuo</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhang%20Wenjun"> Zhang Wenjun </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aiming at the shortcomings of the Quantum Genetic Algorithm such as the multimodal function optimization problems easily falling into the local optimum, and vulnerable to premature convergence due to no closely relationship between individuals, the paper presents an Improved Many Worlds Quantum Genetic Algorithm (IMWQGA). The paper using the concept of Many Worlds; using the derivative way of parallel worlds’ parallel evolution; putting forward the thought which updating the population according to the main body; adopting the transition methods such as parallel transition, backtracking, travel forth. In addition, the algorithm in the paper also proposes the quantum training operator and the combinatorial optimization operator as new operators of quantum genetic algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quantum%20genetic%20algorithm" title="quantum genetic algorithm">quantum genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=many%20worlds" title=" many worlds"> many worlds</a>, <a href="https://publications.waset.org/abstracts/search?q=quantum%20training%20operator" title=" quantum training operator"> quantum training operator</a>, <a href="https://publications.waset.org/abstracts/search?q=combinatorial%20optimization%20operator" title=" combinatorial optimization operator"> combinatorial optimization operator</a> </p> <a href="https://publications.waset.org/abstracts/16842/an-improved-many-worlds-quantum-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16842.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">744</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">3542</span> Multi-Subpopulation Genetic Algorithm with Estimation of Distribution Algorithm for Textile Batch Dyeing Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nhat-To%20Huynh">Nhat-To Huynh</a>, <a href="https://publications.waset.org/abstracts/search?q=Chen-Fu%20Chien"> Chen-Fu Chien</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Textile batch dyeing scheduling problem is complicated which includes batch formation, batch assignment on machines, batch sequencing with sequence-dependent setup time. Most manufacturers schedule their orders manually that are time consuming and inefficient. More power methods are needed to improve the solution. Motivated by the real needs, this study aims to propose approaches in which genetic algorithm is developed with multi-subpopulation and hybridised with estimation of distribution algorithm to solve the constructed problem for minimising the makespan. A heuristic algorithm is designed and embedded into the proposed algorithms to improve the ability to get out of the local optima. In addition, an empirical study is conducted in a textile company in Taiwan to validate the proposed approaches. The results have showed that proposed approaches are more efficient than simulated annealing algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=estimation%20of%20distribution%20algorithm" title="estimation of distribution algorithm">estimation of distribution algorithm</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=multi-subpopulation" title=" multi-subpopulation"> multi-subpopulation</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=textile%20dyeing" title=" textile dyeing"> textile dyeing</a> </p> <a href="https://publications.waset.org/abstracts/66139/multi-subpopulation-genetic-algorithm-with-estimation-of-distribution-algorithm-for-textile-batch-dyeing-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66139.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">299</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">3541</span> A Rapid Code Acquisition Scheme in OOC-Based CDMA Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Keunhong%20Chae">Keunhong Chae</a>, <a href="https://publications.waset.org/abstracts/search?q=Seokho%20Yoon"> Seokho Yoon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose a code acquisition scheme called improved multiple-shift (IMS) for optical code division multiple access systems, where the optical orthogonal code is used instead of the pseudo noise code. Although the IMS algorithm has a similar process to that of the conventional MS algorithm, it has a better code acquisition performance than the conventional MS algorithm. We analyze the code acquisition performance of the IMS algorithm and compare the code acquisition performances of the MS and the IMS algorithms in single-user and multi-user environments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=code%20acquisition" title="code acquisition">code acquisition</a>, <a href="https://publications.waset.org/abstracts/search?q=optical%20CDMA" title=" optical CDMA"> optical CDMA</a>, <a href="https://publications.waset.org/abstracts/search?q=optical%20orthogonal%20code" title=" optical orthogonal code"> optical orthogonal code</a>, <a href="https://publications.waset.org/abstracts/search?q=serial%20algorithm" title=" serial algorithm"> serial algorithm</a> </p> <a href="https://publications.waset.org/abstracts/23348/a-rapid-code-acquisition-scheme-in-ooc-based-cdma-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23348.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">540</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">3540</span> Efficient Heuristic Algorithm to Speed Up Graphcut in Gpu for Image Stitching</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tai%20Nguyen">Tai Nguyen</a>, <a href="https://publications.waset.org/abstracts/search?q=Minh%20Bui"> Minh Bui</a>, <a href="https://publications.waset.org/abstracts/search?q=Huong%20Ninh"> Huong Ninh</a>, <a href="https://publications.waset.org/abstracts/search?q=Tu%20Nguyen"> Tu Nguyen</a>, <a href="https://publications.waset.org/abstracts/search?q=Hai%20Tran"> Hai Tran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> GraphCut algorithm has been widely utilized to solve various types of computer vision problems. Its expensive computational cost encouraged many researchers to improve the speed of the algorithm. Recent works proposed schemes that work on parallel computing platforms such as CUDA. However, the problem of low convergence speed prevents the usage of GraphCut for real time applications. In this paper, we propose global suppression heuristic to boost the conver-gence process of the algorithm. A parallel implementation of GraphCut algorithm on CUDA designed for the image stitching problem is introduced. Our method achieves up to 3× time boost on the graph of size 80 × 480 compared to the best sequential GraphCut algorithm while achieving satisfactory stitched images, suitable for panorama applications. Our source code will be soon available for further research. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CUDA" title="CUDA">CUDA</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20cut" title=" graph cut"> graph cut</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20stitching" title=" image stitching"> image stitching</a>, <a href="https://publications.waset.org/abstracts/search?q=texture%20synthesis" title=" texture synthesis"> texture synthesis</a>, <a href="https://publications.waset.org/abstracts/search?q=maxflow%2Fmincut%20algorithm" title=" maxflow/mincut algorithm"> maxflow/mincut algorithm</a> </p> <a href="https://publications.waset.org/abstracts/154120/efficient-heuristic-algorithm-to-speed-up-graphcut-in-gpu-for-image-stitching" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/154120.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">132</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">3539</span> Travel Planning in Public Transport Networks Applying the Algorithm A* for Metropolitan District of Quito</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Fernanda%20Salgado">M. Fernanda Salgado</a>, <a href="https://publications.waset.org/abstracts/search?q=Alfonso%20Tierra"> Alfonso Tierra</a>, <a href="https://publications.waset.org/abstracts/search?q=Wilbert%20Aguilar"> Wilbert Aguilar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present project consists in applying the informed search algorithm A star (A*) to solve traveler problems, applying it by urban public transportation routes. The digitization of the information allowed to identify 26% of the total of routes that are registered within the Metropolitan District of Quito. For the validation of this information, data were taken in field on the travel times and the difference with respect to the times estimated by the program, resulting in that the difference between them was not greater than 2:20 minutes. We validate A* algorithm with the Dijkstra algorithm, comparing nodes vectors based on the public transport stops, the validation was established through the student t-test hypothesis. Then we verified that the times estimated by the program using the A* algorithm are similar to those registered on field. Furthermore, we review the performance of the algorithm generating iterations in both algorithms. Finally, with these iterations, a hypothesis test was carried out again with student t-test where it was concluded that the iterations of the base algorithm Dijsktra are greater than those generated by the algorithm A*. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=algorithm%20A%2A" title="algorithm A*">algorithm A*</a>, <a href="https://publications.waset.org/abstracts/search?q=graph" title=" graph"> graph</a>, <a href="https://publications.waset.org/abstracts/search?q=mobility" title=" mobility"> mobility</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20transport" title=" public transport"> public transport</a>, <a href="https://publications.waset.org/abstracts/search?q=travel%20planning" title=" travel planning"> travel planning</a>, <a href="https://publications.waset.org/abstracts/search?q=routes" title=" routes"> routes</a> </p> <a href="https://publications.waset.org/abstracts/81275/travel-planning-in-public-transport-networks-applying-the-algorithm-a-for-metropolitan-district-of-quito" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81275.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">239</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">3538</span> Assessment of Memetic and Genetic Algorithm for a Flexible Integrated Logistics Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=E.%20Behmanesh">E. Behmanesh</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Pannek"> J. Pannek</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The distribution-allocation problem is known as one of the most comprehensive strategic decision. In real-world cases, it is impossible to solve a distribution-allocation problem in traditional ways with acceptable time. Hence researchers develop efficient non-traditional techniques for the large-term operation of the whole supply chain. These techniques provide near-optimal solutions particularly for large scales test problems. This paper, presents an integrated supply chain model which is flexible in the delivery path. As the solution methodology, we apply a memetic algorithm with a novelty in population presentation. To illustrate the performance of the proposed memetic algorithm, LINGO optimization software serves as a comparison basis for small size problems. In large size cases that we are dealing with in the real world, the Genetic algorithm as the second metaheuristic algorithm is considered to compare the results and show the efficiency of the memetic algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=integrated%20logistics%20network" title="integrated logistics network">integrated logistics network</a>, <a href="https://publications.waset.org/abstracts/search?q=flexible%20path" title=" flexible path"> flexible path</a>, <a href="https://publications.waset.org/abstracts/search?q=memetic%20algorithm" title=" memetic algorithm"> memetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a> </p> <a href="https://publications.waset.org/abstracts/81478/assessment-of-memetic-and-genetic-algorithm-for-a-flexible-integrated-logistics-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81478.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">374</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">3537</span> A Speeded up Robust Scale-Invariant Feature Transform Currency Recognition Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Daliyah%20S.%20Aljutaili">Daliyah S. Aljutaili</a>, <a href="https://publications.waset.org/abstracts/search?q=Redna%20A.%20Almutlaq"> Redna A. Almutlaq</a>, <a href="https://publications.waset.org/abstracts/search?q=Suha%20A.%20Alharbi"> Suha A. Alharbi</a>, <a href="https://publications.waset.org/abstracts/search?q=Dina%20M.%20Ibrahim"> Dina M. Ibrahim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=currency%20recognition" title="currency recognition">currency recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20detection%20and%20description" title=" feature detection and description"> feature detection and description</a>, <a href="https://publications.waset.org/abstracts/search?q=SIFT%20algorithm" title=" SIFT algorithm"> SIFT algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=SURF%20algorithm" title=" SURF algorithm"> SURF algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=speeded%20up%20and%20robust%20features" title=" speeded up and robust features"> speeded up and robust features</a> </p> <a href="https://publications.waset.org/abstracts/94315/a-speeded-up-robust-scale-invariant-feature-transform-currency-recognition-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94315.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">235</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">3536</span> Features Reduction Using Bat Algorithm for Identification and Recognition of Parkinson Disease </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Shrivastava">P. Shrivastava</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Shukla"> A. Shukla</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Verma"> K. Verma</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Rungta"> S. Rungta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=parkinson" title="parkinson">parkinson</a>, <a href="https://publications.waset.org/abstracts/search?q=gait" title=" gait"> gait</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20selection" title=" feature selection"> feature selection</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/31393/features-reduction-using-bat-algorithm-for-identification-and-recognition-of-parkinson-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31393.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info 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