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algorithms</title> <meta name="description" content="Search results for: adaptive algorithms"> <meta name="keywords" content="adaptive algorithms"> <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 class="d-block d-lg-none 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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="adaptive algorithms"> <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> 2070</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: adaptive algorithms</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2070</span> Acoustic Echo Cancellation Using Different Adaptive Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamid%20Sharif">Hamid Sharif</a>, <a href="https://publications.waset.org/abstracts/search?q=Nazish%20Saleem%20Abbas"> Nazish Saleem Abbas</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Haris%20Jamil"> Muhammad Haris Jamil</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An adaptive filter is a filter that self-adjusts its transfer function according to an optimization algorithm driven by an error signal. Because of the complexity of the optimization algorithms, most adaptive filters are digital filters. Adaptive filtering constitutes one of the core technologies in digital signal processing and finds numerous application areas in science as well as in industry. Adaptive filtering techniques are used in a wide range of applications, including adaptive noise cancellation and echo cancellation. Acoustic echo cancellation is a common occurrence in today’s telecommunication systems. The signal interference caused by acoustic echo is distracting to both users and causes a reduction in the quality of the communication. In this paper, we review different techniques of adaptive filtering to reduce this unwanted echo. In this paper, we see the behavior of techniques and algorithms of adaptive filtering like Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Variable Step-Size Least Mean Square (VSLMS), Variable Step-Size Normalized Least Mean Square (VSNLMS), New Varying Step Size LMS Algorithm (NVSSLMS) and Recursive Least Square (RLS) algorithms to reduce this unwanted echo, to increase communication quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20acoustic" title="adaptive acoustic">adaptive acoustic</a>, <a href="https://publications.waset.org/abstracts/search?q=echo%20cancellation" title=" echo cancellation"> echo cancellation</a>, <a href="https://publications.waset.org/abstracts/search?q=LMS%20algorithm" title=" LMS algorithm"> LMS algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filter" title=" adaptive filter"> adaptive filter</a>, <a href="https://publications.waset.org/abstracts/search?q=normalized%20least%20mean%20square%20%28NLMS%29" title=" normalized least mean square (NLMS)"> normalized least mean square (NLMS)</a>, <a href="https://publications.waset.org/abstracts/search?q=variable%20step-size%20least%20mean%20square%20%28VSLMS%29" title=" variable step-size least mean square (VSLMS)"> variable step-size least mean square (VSLMS)</a> </p> <a href="https://publications.waset.org/abstracts/167766/acoustic-echo-cancellation-using-different-adaptive-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/167766.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">80</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">2069</span> Study of Adaptive Filtering Algorithms and the Equalization of Radio Mobile Channel</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Said%20Elkassimi">Said Elkassimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Said%20Safi"> Said Safi</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Manaut"> B. Manaut</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filtering%20second%20equalizer" title="adaptive filtering second equalizer">adaptive filtering second equalizer</a>, <a href="https://publications.waset.org/abstracts/search?q=LMS" title=" LMS"> LMS</a>, <a href="https://publications.waset.org/abstracts/search?q=RLS%20%20Bran%20A" title=" RLS Bran A"> RLS Bran A</a>, <a href="https://publications.waset.org/abstracts/search?q=Proakis%20%28B%29%20MMSE" title=" Proakis (B) MMSE"> Proakis (B) MMSE</a>, <a href="https://publications.waset.org/abstracts/search?q=ZF" title=" ZF"> ZF</a> </p> <a href="https://publications.waset.org/abstracts/32853/study-of-adaptive-filtering-algorithms-and-the-equalization-of-radio-mobile-channel" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32853.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">313</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">2068</span> An Overview of Adaptive Channel Equalization Techniques and Algorithms</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> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless communication system has been proved as the best for any communication. However, there are some undesirable threats of a wireless communication channel on the information transmitted through it, such as attenuation, distortions, delays and phase shifts of the signals arriving at the receiver end which are caused by its band limited and dispersive nature. One of the threat is ISI (Inter Symbol Interference), which has been found as a great obstacle in high speed communication. Thus, there is a need to provide perfect and accurate technique to remove this effect to have an error free communication. Thus, different equalization techniques have been proposed in literature. This paper presents the equalization techniques followed by the concept of adaptive filter equalizer, its algorithms (LMS and RLS) and applications of adaptive equalization technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=channel%20equalization" title="channel equalization">channel equalization</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20equalizer" title=" adaptive equalizer"> adaptive equalizer</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20mean%20square" title=" least mean square"> least mean square</a>, <a href="https://publications.waset.org/abstracts/search?q=recursive%20least%20square" title=" recursive least square"> recursive least square</a> </p> <a href="https://publications.waset.org/abstracts/9270/an-overview-of-adaptive-channel-equalization-techniques-and-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9270.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">450</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">2067</span> Equity Risk Premiums and Risk Free Rates in Modelling and Prediction of Financial Markets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Ghavami">Mohammad Ghavami</a>, <a href="https://publications.waset.org/abstracts/search?q=Reza%20S.%20Dilmaghani"> Reza S. Dilmaghani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20methods" title="adaptive methods">adaptive methods</a>, <a href="https://publications.waset.org/abstracts/search?q=LSE" title=" LSE"> LSE</a>, <a href="https://publications.waset.org/abstracts/search?q=MSE" title=" MSE"> MSE</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction%20of%20financial%20Markets" title=" prediction of financial Markets"> prediction of financial Markets</a> </p> <a href="https://publications.waset.org/abstracts/72693/equity-risk-premiums-and-risk-free-rates-in-modelling-and-prediction-of-financial-markets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72693.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">2066</span> Performance Comparisons between PID and Adaptive PID Controllers for Travel Angle Control of a Bench-Top Helicopter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Mansor">H. Mansor</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20B.%20Mohd-Noor"> S. B. Mohd-Noor</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20S.%20Gunawan"> T. S. Gunawan</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Khan"> S. Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20I.%20Othman"> N. I. Othman</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Tazali"> N. Tazali</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20B.%20Islam"> R. B. Islam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper provides a comparative study on the performances of standard PID and adaptive PID controllers tested on travel angle of a 3-Degree-of-Freedom (3-DOF) Quanser bench-top helicopter. Quanser, a well-known manufacturer of educational bench-top helicopter has developed Proportional Integration Derivative (PID) controller with Linear Quadratic Regulator (LQR) for all travel, pitch and yaw angle of the bench-top helicopter. The performance of the PID controller is relatively good; however its performance could also be improved if the controller is combined with adaptive element. The objective of this research is to design adaptive PID controller and then compare the performances of the adaptive PID with the standard PID. The controller design and test is focused on travel angle control only. Adaptive method used in this project is self-tuning controller, which controller’s parameters are updated online. Two adaptive algorithms those are pole-placement and deadbeat have been chosen as the method to achieve optimal controller’s parameters. Performance comparisons have shown that the adaptive (deadbeat) PID controller has produced more desirable performance compared to standard PID and adaptive (pole-placement). The adaptive (deadbeat) PID controller attained very fast settling time (5 seconds) and very small percentage of overshoot (5% to 7.5%) for 10° to 30° step change of travel angle. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20control" title="adaptive control">adaptive control</a>, <a href="https://publications.waset.org/abstracts/search?q=deadbeat" title=" deadbeat"> deadbeat</a>, <a href="https://publications.waset.org/abstracts/search?q=pole-placement" title=" pole-placement"> pole-placement</a>, <a href="https://publications.waset.org/abstracts/search?q=bench-top%20helicopter" title=" bench-top helicopter"> bench-top helicopter</a>, <a href="https://publications.waset.org/abstracts/search?q=self-tuning%20control" title=" self-tuning control"> self-tuning control</a> </p> <a href="https://publications.waset.org/abstracts/15094/performance-comparisons-between-pid-and-adaptive-pid-controllers-for-travel-angle-control-of-a-bench-top-helicopter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15094.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">501</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">2065</span> Application of Regularized Low-Rank Matrix Factorization in Personalized Targeting </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kourosh%20Modarresi">Kourosh Modarresi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Netflix problem has brought the topic of “Recommendation Systems” into the mainstream of computer science, mathematics, and statistics. Though much progress has been made, the available algorithms do not obtain satisfactory results. The success of these algorithms is rarely above 5%. This work is based on the belief that the main challenge is to come up with “scalable personalization” models. This paper uses an adaptive regularization of inverse singular value decomposition (SVD) that applies adaptive penalization on the singular vectors. The results show far better matching for recommender systems when compared to the ones from the state of the art models in the industry. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=convex%20optimization" title="convex optimization">convex optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=LASSO" title=" LASSO"> LASSO</a>, <a href="https://publications.waset.org/abstracts/search?q=regression" title=" regression"> regression</a>, <a href="https://publications.waset.org/abstracts/search?q=recommender%20systems" title=" recommender systems"> recommender systems</a>, <a href="https://publications.waset.org/abstracts/search?q=singular%20value%20decomposition" title=" singular value decomposition"> singular value decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=low%20rank%20approximation" title=" low rank approximation"> low rank approximation</a> </p> <a href="https://publications.waset.org/abstracts/19547/application-of-regularized-low-rank-matrix-factorization-in-personalized-targeting" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19547.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">455</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">2064</span> Comparison of ANFIS Update Methods Using Genetic Algorithm, Particle Swarm Optimization, and Artificial Bee Colony</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Michael%20R.%20Phangtriastu">Michael R. Phangtriastu</a>, <a href="https://publications.waset.org/abstracts/search?q=Herriyandi%20Herriyandi"> Herriyandi Herriyandi</a>, <a href="https://publications.waset.org/abstracts/search?q=Diaz%20D.%20Santika"> Diaz D. Santika</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a comparison of the implementation of metaheuristic algorithms to train the antecedent parameters and consequence parameters in the adaptive network-based fuzzy inference system (ANFIS). The algorithms compared are genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC). The objective of this paper is to benchmark well-known metaheuristic algorithms. The algorithms are applied to several data set with different nature. The combinations of the algorithms' parameters are tested. In all algorithms, a different number of populations are tested. In PSO, combinations of velocity are tested. In ABC, a different number of limit abandonment are tested. Experiments find out that ABC is more reliable than other algorithms, ABC manages to get better mean square error (MSE) than other algorithms in all data set. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ANFIS" title="ANFIS">ANFIS</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20bee%20colony" title=" artificial bee colony"> artificial bee colony</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=metaheuristic%20algorithm" title=" metaheuristic algorithm"> metaheuristic algorithm</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/68821/comparison-of-anfis-update-methods-using-genetic-algorithm-particle-swarm-optimization-and-artificial-bee-colony" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68821.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">2063</span> Neuroevolution Based on Adaptive Ensembles of Biologically Inspired Optimization Algorithms Applied for Modeling a Chemical Engineering Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sabina-Adriana%20Floria">Sabina-Adriana Floria</a>, <a href="https://publications.waset.org/abstracts/search?q=Marius%20Gavrilescu"> Marius Gavrilescu</a>, <a href="https://publications.waset.org/abstracts/search?q=Florin%20Leon"> Florin Leon</a>, <a href="https://publications.waset.org/abstracts/search?q=Silvia%20Curteanu"> Silvia Curteanu</a>, <a href="https://publications.waset.org/abstracts/search?q=Costel%20Anton"> Costel Anton</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values. <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=biologically%20inspired%20algorithm" title=" biologically inspired algorithm"> biologically inspired algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=neuroevolution" title=" neuroevolution"> neuroevolution</a>, <a href="https://publications.waset.org/abstracts/search?q=ensembles" title=" ensembles"> ensembles</a>, <a href="https://publications.waset.org/abstracts/search?q=bricks" title=" bricks"> bricks</a>, <a href="https://publications.waset.org/abstracts/search?q=emission%20minimization" title=" emission minimization"> emission minimization</a> </p> <a href="https://publications.waset.org/abstracts/162135/neuroevolution-based-on-adaptive-ensembles-of-biologically-inspired-optimization-algorithms-applied-for-modeling-a-chemical-engineering-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162135.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">116</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">2062</span> Towards a Computational Model of Consciousness: Global Abstraction Workspace</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Halim%20Djerroud">Halim Djerroud</a>, <a href="https://publications.waset.org/abstracts/search?q=Arab%20Ali%20Cherif"> Arab Ali Cherif</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We assume that conscious functions are implemented automatically. In other words that consciousness as well as the non-consciousness aspect of human thought, planning, and perception, are produced by biologically adaptive algorithms. We propose that the mechanisms of consciousness can be produced using similar adaptive algorithms to those executed by the mechanism. In this paper, we propose a computational model of consciousness, the ”Global Abstraction Workspace” which is an internal environmental modelling perceived as a multi-agent system. This system is able to evolve and generate new data and processes as well as actions in the environment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20consciousness" title="artificial consciousness">artificial consciousness</a>, <a href="https://publications.waset.org/abstracts/search?q=cognitive%20architecture" title=" cognitive architecture"> cognitive architecture</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20abstraction%20workspace" title=" global abstraction workspace"> global abstraction workspace</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-agent%20system" title=" multi-agent system"> multi-agent system</a> </p> <a href="https://publications.waset.org/abstracts/63955/towards-a-computational-model-of-consciousness-global-abstraction-workspace" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63955.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">340</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">2061</span> An Observer-Based Direct Adaptive Fuzzy Sliding Control with Adjustable Membership Functions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alireza%20Gholami">Alireza Gholami</a>, <a href="https://publications.waset.org/abstracts/search?q=Amir%20H.%20D.%20Markazi"> Amir H. D. Markazi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20algorithm" title="adaptive algorithm">adaptive algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20systems" title=" fuzzy systems"> fuzzy systems</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20functions" title=" membership functions"> membership functions</a>, <a href="https://publications.waset.org/abstracts/search?q=observer" title=" observer"> observer</a> </p> <a href="https://publications.waset.org/abstracts/81807/an-observer-based-direct-adaptive-fuzzy-sliding-control-with-adjustable-membership-functions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81807.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">206</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">2060</span> Comparison Analysis of Multi-Channel Echo Cancellation Using Adaptive Filters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sahar%20Mobeen">Sahar Mobeen</a>, <a href="https://publications.waset.org/abstracts/search?q=Anam%20Rafique"> Anam Rafique</a>, <a href="https://publications.waset.org/abstracts/search?q=Irum%20Baig"> Irum Baig</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Acoustic echo cancellation in multichannel is a system identification application. In real time environment, signal changes very rapidly which required adaptive algorithms such as Least Mean Square (LMS), Leaky Least Mean Square (LLMS), Normalized Least Mean square (NLMS) and average (AFA) having high convergence rate and stable. LMS and NLMS are widely used adaptive algorithm due to less computational complexity and AFA used of its high convergence rate. This research is based on comparison of acoustic echo (generated in a room) cancellation thorough LMS, LLMS, NLMS, AFA and newly proposed average normalized leaky least mean square (ANLLMS) adaptive filters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=LMS" title="LMS">LMS</a>, <a href="https://publications.waset.org/abstracts/search?q=LLMS" title=" LLMS"> LLMS</a>, <a href="https://publications.waset.org/abstracts/search?q=NLMS" title=" NLMS"> NLMS</a>, <a href="https://publications.waset.org/abstracts/search?q=AFA" title=" AFA"> AFA</a>, <a href="https://publications.waset.org/abstracts/search?q=ANLLMS" title=" ANLLMS"> ANLLMS</a> </p> <a href="https://publications.waset.org/abstracts/28829/comparison-analysis-of-multi-channel-echo-cancellation-using-adaptive-filters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28829.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">566</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">2059</span> Adaptive CFAR Analysis for Non-Gaussian Distribution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bouchemha%20Amel">Bouchemha Amel</a>, <a href="https://publications.waset.org/abstracts/search?q=Chachoui%20Takieddine"> Chachoui Takieddine</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Maalem"> H. Maalem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Automatic detection of targets in a modern communication system RADAR is based primarily on the concept of adaptive CFAR detector. To have an effective detection, we must minimize the influence of disturbances due to the clutter. The detection algorithm adapts the CFAR detection threshold which is proportional to the average power of the clutter, maintaining a constant probability of false alarm. In this article, we analyze the performance of two variants of adaptive algorithms CA-CFAR and OS-CFAR and we compare the thresholds of these detectors in the marine environment (no-Gaussian) with a Weibull distribution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CFAR" title="CFAR">CFAR</a>, <a href="https://publications.waset.org/abstracts/search?q=threshold" title=" threshold"> threshold</a>, <a href="https://publications.waset.org/abstracts/search?q=clutter" title=" clutter"> clutter</a>, <a href="https://publications.waset.org/abstracts/search?q=distribution" title=" distribution"> distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=Weibull" title=" Weibull"> Weibull</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a> </p> <a href="https://publications.waset.org/abstracts/21359/adaptive-cfar-analysis-for-non-gaussian-distribution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21359.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">588</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">2058</span> Preliminary Proposal to Use Adaptive Computer Games in the Virtual Rehabilitation Therapy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mamoun%20S.%20Ideis">Mamoun S. Ideis</a>, <a href="https://publications.waset.org/abstracts/search?q=Zein%20Salah"> Zein Salah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Virtual Rehabilitation (VR) refers to using Virtual Reality’s hardware and simulations as means of exercising tools to rehabilitate patients in need. These patients will undergo their treatment exercises while playing different computer games, which helps achieve greater motivation for patients undergoing their therapeutic exercises. Virtual Rehabilitation systems adopt computer games as part of the treatment therapy. In this paper, we present a preliminary proposal to using adaptive computer games in Virtual Rehabilitation therapy. We also present some tips in designing those adaptive computer games by using different machine learning algorithms in order to create a personalized experience for each patient, which in turn, increases the potential benefits of the treatment that each patient receives. Furthermore, we propose a method of comparing the results of treatment using the adaptive computer games with the results of using static and classical computer games. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=virtual%20rehabilitation" title="virtual rehabilitation">virtual rehabilitation</a>, <a href="https://publications.waset.org/abstracts/search?q=physiotherapy" title=" physiotherapy"> physiotherapy</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20computer%20games" title=" adaptive computer games"> adaptive computer games</a>, <a href="https://publications.waset.org/abstracts/search?q=post-stroke" title=" post-stroke"> post-stroke</a>, <a href="https://publications.waset.org/abstracts/search?q=game%20design" title=" game design"> game design</a> </p> <a href="https://publications.waset.org/abstracts/94427/preliminary-proposal-to-use-adaptive-computer-games-in-the-virtual-rehabilitation-therapy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94427.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">297</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">2057</span> Adaptive Swarm Balancing Algorithms for Rare-Event Prediction in Imbalanced Healthcare Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jinyan%20Li">Jinyan Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Simon%20Fong"> Simon Fong</a>, <a href="https://publications.waset.org/abstracts/search?q=Raymond%20Wong"> Raymond Wong</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Sabah"> Mohammed Sabah</a>, <a href="https://publications.waset.org/abstracts/search?q=Fiaidhi%20Jinan"> Fiaidhi Jinan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Imbalanced%20dataset" title="Imbalanced dataset">Imbalanced dataset</a>, <a href="https://publications.waset.org/abstracts/search?q=meta-heuristic%20algorithm" title=" meta-heuristic algorithm"> meta-heuristic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=SMOTE" title=" SMOTE"> SMOTE</a>, <a href="https://publications.waset.org/abstracts/search?q=big%20data" title=" big data "> big data </a> </p> <a href="https://publications.waset.org/abstracts/41481/adaptive-swarm-balancing-algorithms-for-rare-event-prediction-in-imbalanced-healthcare-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41481.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">441</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">2056</span> An Adaptive Hybrid Surrogate-Assisted Particle Swarm Optimization Algorithm for Expensive Structural Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xiongxiong%20You">Xiongxiong You</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhanwen%20Niu"> Zhanwen Niu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20selection" title="adaptive selection">adaptive selection</a>, <a href="https://publications.waset.org/abstracts/search?q=expensive%20optimization" title=" expensive optimization"> expensive optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=rotor%20system" title=" rotor system"> rotor system</a>, <a href="https://publications.waset.org/abstracts/search?q=surrogates%20assisted%20evolutionary%20algorithms" title=" surrogates assisted evolutionary algorithms"> surrogates assisted evolutionary algorithms</a> </p> <a href="https://publications.waset.org/abstracts/137516/an-adaptive-hybrid-surrogate-assisted-particle-swarm-optimization-algorithm-for-expensive-structural-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/137516.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">141</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">2055</span> Overview of Adaptive Spline interpolation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rongli%20Gai">Rongli Gai</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhiyuan%20Chang"> Zhiyuan Chang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> At this stage, in view of various situations in the interpolation process, most researchers use self-adaptation to adjust the interpolation process, which is also one of the current and future research hotspots in the field of CNC machining. In the interpolation process, according to the overview of the spline curve interpolation algorithm, the adaptive analysis is carried out from the factors affecting the interpolation process. The adaptive operation is reflected in various aspects, such as speed, parameters, errors, nodes, feed rates, random Period, sensitive point, step size, curvature, adaptive segmentation, adaptive optimization, etc. This paper will analyze and summarize the research of adaptive imputation in the direction of the above factors affecting imputation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20algorithm" title="adaptive algorithm">adaptive algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=CNC%20machining" title=" CNC machining"> CNC machining</a>, <a href="https://publications.waset.org/abstracts/search?q=interpolation%20constraints" title=" interpolation constraints"> interpolation constraints</a>, <a href="https://publications.waset.org/abstracts/search?q=spline%20curve%20interpolation" title=" spline curve interpolation"> spline curve interpolation</a> </p> <a href="https://publications.waset.org/abstracts/147139/overview-of-adaptive-spline-interpolation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147139.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">205</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">2054</span> Adaptive Energy-Aware Routing (AEAR) for Optimized Performance in Resource-Constrained Wireless Sensor Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Innocent%20Uzougbo%20Onwuegbuzie">Innocent Uzougbo Onwuegbuzie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless Sensor Networks (WSNs) are crucial for numerous applications, yet they face significant challenges due to resource constraints such as limited power and memory. Traditional routing algorithms like Dijkstra, Ad hoc On-Demand Distance Vector (AODV), and Bellman-Ford, while effective in path establishment and discovery, are not optimized for the unique demands of WSNs due to their large memory footprint and power consumption. This paper introduces the Adaptive Energy-Aware Routing (AEAR) model, a solution designed to address these limitations. AEAR integrates reactive route discovery, localized decision-making using geographic information, energy-aware metrics, and dynamic adaptation to provide a robust and efficient routing strategy. We present a detailed comparative analysis using a dataset of 50 sensor nodes, evaluating power consumption, memory footprint, and path cost across AEAR, Dijkstra, AODV, and Bellman-Ford algorithms. Our results demonstrate that AEAR significantly reduces power consumption and memory usage while optimizing path weight. This improvement is achieved through adaptive mechanisms that balance energy efficiency and link quality, ensuring prolonged network lifespan and reliable communication. The AEAR model's superior performance underlines its potential as a viable routing solution for energy-constrained WSN environments, paving the way for more sustainable and resilient sensor network deployments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wireless%20sensor%20networks%20%28WSNs%29" title="wireless sensor networks (WSNs)">wireless sensor networks (WSNs)</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20energy-aware%20routing%20%28AEAR%29" title=" adaptive energy-aware routing (AEAR)"> adaptive energy-aware routing (AEAR)</a>, <a href="https://publications.waset.org/abstracts/search?q=routing%20algorithms" title=" routing algorithms"> routing algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=energy" title=" energy"> energy</a>, <a href="https://publications.waset.org/abstracts/search?q=efficiency" title=" efficiency"> efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20lifespan" title=" network lifespan"> network lifespan</a> </p> <a href="https://publications.waset.org/abstracts/188257/adaptive-energy-aware-routing-aear-for-optimized-performance-in-resource-constrained-wireless-sensor-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/188257.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">36</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">2053</span> A Novel RLS Based Adaptive Filtering Method for Speech Enhancement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pogula%20Rakesh">Pogula Rakesh</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Kishore%20Kumar"> T. Kishore Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filter" title="adaptive filter">adaptive filter</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20noise%20canceller" title=" adaptive noise canceller"> adaptive noise canceller</a>, <a href="https://publications.waset.org/abstracts/search?q=mean%20squared%20error" title=" mean squared error"> mean squared error</a>, <a href="https://publications.waset.org/abstracts/search?q=noise%20reduction" title=" noise reduction"> noise reduction</a>, <a href="https://publications.waset.org/abstracts/search?q=NLMS" title=" NLMS"> NLMS</a>, <a href="https://publications.waset.org/abstracts/search?q=RLS" title=" RLS"> RLS</a>, <a href="https://publications.waset.org/abstracts/search?q=SNR" title=" SNR"> SNR</a>, <a href="https://publications.waset.org/abstracts/search?q=SNR%20loss" title=" SNR loss"> SNR loss</a> </p> <a href="https://publications.waset.org/abstracts/16212/a-novel-rls-based-adaptive-filtering-method-for-speech-enhancement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16212.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">481</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">2052</span> The Adaptive Properties of the Strategic Assurance System of the National Economy Sustainability to the Economic Security Threats</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Badri%20Gechbaia">Badri Gechbaia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Adaptive management as a fundamental element of the concept of the assurance of economy`s sustainability to the economic security of the system-synergetic type has been considered. It has been proved that the adaptive sustainable development is a transitional phase from the extensive one and later on from the rapid growth to the sustainable development. It has been determined that the adaptive system of the strategic assurance of the sustainability of the economy to the economic security threats is formed on the principles of the domination in its complex of the subsystems with weightier adaptive characteristics that negate the destructive influence of external and internal environmental factors on the sustainability of the national economy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20management" title="adaptive management">adaptive management</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20properties" title=" adaptive properties"> adaptive properties</a>, <a href="https://publications.waset.org/abstracts/search?q=economic%20security" title=" economic security"> economic security</a>, <a href="https://publications.waset.org/abstracts/search?q=strategic%20assurance" title=" strategic assurance "> strategic assurance </a> </p> <a href="https://publications.waset.org/abstracts/35350/the-adaptive-properties-of-the-strategic-assurance-system-of-the-national-economy-sustainability-to-the-economic-security-threats" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35350.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">507</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">2051</span> Adaptive Dehazing Using Fusion Strategy </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Ramesh%20Kanthan">M. Ramesh Kanthan</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Naga%20Nandini%20Sujatha"> S. Naga Nandini Sujatha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The goal of haze removal algorithms is to enhance and recover details of scene from foggy image. In enhancement the proposed method focus into two main categories: (i) image enhancement based on Adaptive contrast Histogram equalization, and (ii) image edge strengthened Gradient model. Many circumstances accurate haze removal algorithms are needed. The de-fog feature works through a complex algorithm which first determines the fog destiny of the scene, then analyses the obscured image before applying contrast and sharpness adjustments to the video in real-time to produce image the fusion strategy is driven by the intrinsic properties of the original image and is highly dependent on the choice of the inputs and the weights. Then the output haze free image has reconstructed using fusion methodology. In order to increase the accuracy, interpolation method has used in the output reconstruction. A promising retrieval performance is achieved especially in particular examples. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=single%20image" title="single image">single image</a>, <a href="https://publications.waset.org/abstracts/search?q=fusion" title=" fusion"> fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=dehazing" title=" dehazing"> dehazing</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-scale%20fusion" title=" multi-scale fusion"> multi-scale fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=per-pixel" title=" per-pixel"> per-pixel</a>, <a href="https://publications.waset.org/abstracts/search?q=weight%20map" title=" weight map"> weight map</a> </p> <a href="https://publications.waset.org/abstracts/32544/adaptive-dehazing-using-fusion-strategy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32544.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">464</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">2050</span> Design and Implementation a Platform for Adaptive Online Learning Based on Fuzzy Logic</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Budoor%20Al%20Abid">Budoor Al Abid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only. <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=adaptive" title=" adaptive"> adaptive</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=data%20mining" title=" data mining"> data mining</a> </p> <a href="https://publications.waset.org/abstracts/139852/design-and-implementation-a-platform-for-adaptive-online-learning-based-on-fuzzy-logic" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/139852.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">196</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">2049</span> Model Reference Adaptive Control and LQR Control for Quadrotor with Parametric Uncertainties</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alia%20Abdul%20Ghaffar">Alia Abdul Ghaffar</a>, <a href="https://publications.waset.org/abstracts/search?q=Tom%20Richardson"> Tom Richardson</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A model reference adaptive control and a fixed gain LQR control were implemented in the height controller of a quadrotor that has parametric uncertainties due to the act of picking up an object of unknown dimension and mass. It is shown that an adaptive control, unlike a fixed gain control, is capable of ensuring a stable tracking performance under such condition, although adaptive control suffers from several limitations. The combination of both adaptive and fixed gain control in the controller architecture results in an enhanced tracking performance in the presence of parametric uncertainties. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=UAV" title="UAV">UAV</a>, <a href="https://publications.waset.org/abstracts/search?q=quadrotor" title=" quadrotor"> quadrotor</a>, <a href="https://publications.waset.org/abstracts/search?q=robotic%20arm%20augmentation" title=" robotic arm augmentation"> robotic arm augmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20reference%20adaptive%20control" title=" model reference adaptive control"> model reference adaptive control</a>, <a href="https://publications.waset.org/abstracts/search?q=LQR%20control" title=" LQR control"> LQR control</a> </p> <a href="https://publications.waset.org/abstracts/14946/model-reference-adaptive-control-and-lqr-control-for-quadrotor-with-parametric-uncertainties" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14946.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">472</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">2048</span> Item Response Calibration/Estimation: An Approach to Adaptive E-Learning System Development</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adeniran%20Adetunji">Adeniran Adetunji</a>, <a href="https://publications.waset.org/abstracts/search?q=Babalola%20M.%20Florence"> Babalola M. Florence</a>, <a href="https://publications.waset.org/abstracts/search?q=Akande%20Ademola"> Akande Ademola</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we made an overview on the concept of adaptive e-Learning system, enumerates the elements of adaptive learning concepts e.g. A pedagogical framework, multiple learning strategies and pathways, continuous monitoring and feedback on student performance, statistical inference to reach final learning strategy that works for an individual learner by “mass-customization”. Briefly highlights the motivation of this new system proposed for effective learning teaching. E-Review literature on the concept of adaptive e-learning system and emphasises on the Item Response Calibration, which is an important approach to developing an adaptive e-Learning system. This paper write-up is concluded on the justification of item response calibration/estimation towards designing a successful and effective adaptive e-Learning system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20e-learning%20system" title="adaptive e-learning system">adaptive e-learning system</a>, <a href="https://publications.waset.org/abstracts/search?q=pedagogical%20framework" title=" pedagogical framework"> pedagogical framework</a>, <a href="https://publications.waset.org/abstracts/search?q=item%20response" title=" item response"> item response</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20applications" title=" computer applications"> computer applications</a> </p> <a href="https://publications.waset.org/abstracts/5647/item-response-calibrationestimation-an-approach-to-adaptive-e-learning-system-development" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5647.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">595</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">2047</span> Hierarchical Clustering Algorithms in Data Mining</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Z.%20Abdullah">Z. Abdullah</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20R.%20Hamdan"> A. R. Hamdan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Clustering is a process of grouping objects and data into groups of clusters to ensure that data objects from the same cluster are identical to each other. Clustering algorithms in one of the areas in data mining and it can be classified into partition, hierarchical, density based, and grid-based. Therefore, in this paper, we do a survey and review for four major hierarchical clustering algorithms called CURE, ROCK, CHAMELEON, and BIRCH. The obtained state of the art of these algorithms will help in eliminating the current problems, as well as deriving more robust and scalable algorithms for clustering. <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=unsupervised%20learning" title=" unsupervised learning"> unsupervised learning</a>, <a href="https://publications.waset.org/abstracts/search?q=algorithms" title=" algorithms"> algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=hierarchical" title=" hierarchical"> hierarchical</a> </p> <a href="https://publications.waset.org/abstracts/31217/hierarchical-clustering-algorithms-in-data-mining" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31217.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">885</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">2046</span> Intelligent Adaptive Learning in a Changing Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20Valentis">G. Valentis</a>, <a href="https://publications.waset.org/abstracts/search?q=Q.%20Berthelot"> Q. Berthelot</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays the trend to develop ever more intelligent and autonomous systems often takes its inspiration in the living beings on Earth. Some simple isolated systems are able, once brought together, to form a strong and reliable system. When trying to adapt the idea to man-made systems it is not possible to include in their program everything the system may encounter during its life cycle. It is, thus, necessary to make the system able to take decisions based on other criteria such as its past experience, i.e. to make the system learn on its own. However, at some point the acquired knowledge depends also on environment. So the question is: if system environment is modified, how could the system respond to it quickly and appropriately enough? Here, starting from reinforcement learning to rate its decisions, and using adaptive learning algorithms for gain and loss reward, the system is made able to respond to changing environment and to adapt its knowledge as time passes. Application is made to a robot finding an exit in a labyrinth. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reinforcement%20learning" title="reinforcement learning">reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=autonomous%20systems" title=" autonomous systems"> autonomous systems</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20learning" title=" adaptive learning"> adaptive learning</a>, <a href="https://publications.waset.org/abstracts/search?q=changing%20environment" title=" changing environment"> changing environment</a> </p> <a href="https://publications.waset.org/abstracts/13941/intelligent-adaptive-learning-in-a-changing-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13941.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">424</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">2045</span> Comparison of Presented Definitions and Aspects of Authenticity and Integrity in Adaptive Reuse</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Golnaz%20Salehi%20Mourkani">Golnaz Salehi Mourkani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Two conception of Integrity and authenticity, in texts have just applied respectively for adaptive reuse and conservation, which in comparison with word “Integrity” in texts related to adaptive reuse is much more seen than Authenticity, which is often applied with conservation. According to Stove, H. (2007) in some cases, this conception have used with this form “integrity/authenticity” in texts, that cause to infer one conception of both. In this article, with referring to definitions and comparison of aspects specialized to both concept of “Authenticity and Integrity” through literature review, it was attempted to examine common and distinctive aspects of each one, then with this method we can reach their differences in adaptive reuse. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20reuse" title="adaptive reuse">adaptive reuse</a>, <a href="https://publications.waset.org/abstracts/search?q=integrity" title=" integrity"> integrity</a>, <a href="https://publications.waset.org/abstracts/search?q=authenticity" title=" authenticity"> authenticity</a>, <a href="https://publications.waset.org/abstracts/search?q=conservation" title=" conservation"> conservation</a> </p> <a href="https://publications.waset.org/abstracts/18769/comparison-of-presented-definitions-and-aspects-of-authenticity-and-integrity-in-adaptive-reuse" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18769.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">460</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">2044</span> Adaptive Cooperative Control of Nonholonomic Mobile Robot Based on Immersion and Invariance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Imil%20Hamda%20Imran">Imil Hamda Imran</a>, <a href="https://publications.waset.org/abstracts/search?q=Sami%20El%20Ferik"> Sami El Ferik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with adaptive cooperative control of non holonomic mobile robot moved together in a given formation. The controller is designed based on the Immersion and Invariance (I&I) approach. I&I is a framework for adaptive stabilization of nonlinear systems with uncertain parameters. We investigate the tracking control of non holonomic mobile robot with uncertainties in The I&I-based adaptive controller regulates the angular and linear velocity of non holonomic mobile robot. The results demonstrate that the ability of I&I-based adaptive cooperative control in tracking the position of non holonomic mobile robot. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nonholonomic%20mobile%20robot" title="nonholonomic mobile robot">nonholonomic mobile robot</a>, <a href="https://publications.waset.org/abstracts/search?q=immersion%20and%20invariance" title=" immersion and invariance"> immersion and invariance</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20control" title=" adaptive control"> adaptive control</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertain%20nonlinear%20systems" title=" uncertain nonlinear systems"> uncertain nonlinear systems</a> </p> <a href="https://publications.waset.org/abstracts/21832/adaptive-cooperative-control-of-nonholonomic-mobile-robot-based-on-immersion-and-invariance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21832.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">499</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">2043</span> Improvement of the Numerical Integration's Quality in Meshless Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahlem%20Mougaida">Ahlem Mougaida</a>, <a href="https://publications.waset.org/abstracts/search?q=Hedi%20Bel%20Hadj%20Salah"> Hedi Bel Hadj Salah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Several methods are suggested to improve the numerical integration in Galerkin weak form for Meshless methods. In fact, integrating without taking into account the characteristics of the shape functions reproduced by Meshless methods (rational functions, with compact support etc.), causes a large integration error that influences the PDE’s approximate solution. Comparisons between different methods of numerical integration for rational functions are discussed and compared. The algorithms are implemented in Matlab. Finally, numerical results were presented to prove the efficiency of our algorithms in improving results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20methods" title="adaptive methods">adaptive methods</a>, <a href="https://publications.waset.org/abstracts/search?q=meshless" title=" meshless"> meshless</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20integration" title=" numerical integration"> numerical integration</a>, <a href="https://publications.waset.org/abstracts/search?q=rational%20quadrature" title=" rational quadrature"> rational quadrature</a> </p> <a href="https://publications.waset.org/abstracts/46442/improvement-of-the-numerical-integrations-quality-in-meshless-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46442.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">364</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">2042</span> Fault Diagnosis of Manufacturing Systems Using AntTreeStoch with Parameter Optimization by ACO</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ouahab%20Kadri">Ouahab Kadri</a>, <a href="https://publications.waset.org/abstracts/search?q=Leila%20Hayet%20Mouss"> Leila Hayet Mouss</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present three diagnostic modules for complex and dynamic systems. These modules are based on three ant colony algorithms, which are AntTreeStoch, Lumer & Faieta and Binary ant colony. We chose these algorithms for their simplicity and their wide application range. However, we cannot use these algorithms in their basement forms as they have several limitations. To use these algorithms in a diagnostic system, we have proposed three variants. We have tested these algorithms on datasets issued from two industrial systems, which are clinkering system and pasteurization system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ant%20colony%20algorithms" title="ant colony algorithms">ant colony algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=complex%20and%20dynamic%20systems" title=" complex and dynamic systems"> complex and dynamic systems</a>, <a href="https://publications.waset.org/abstracts/search?q=diagnosis" title=" diagnosis"> diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/42293/fault-diagnosis-of-manufacturing-systems-using-anttreestoch-with-parameter-optimization-by-aco" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42293.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">298</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">2041</span> Adaptive Thermal Comfort Model for Air-Conditioned Lecture Halls in Malaysia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20T.%20Chew">B. T. Chew</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20N.%20Kazi"> S. N. Kazi</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Amiri"> A. Amiri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an adaptive thermal comfort model study in the tropical country of Malaysia. A number of researchers have been interested in applying the adaptive thermal comfort model to different climates throughout the world, but so far no study has been performed in Malaysia. For the use as a thermal comfort model, which better applies to hot and humid climates, the adaptive thermal comfort model was developed as part of this research by using the collected results from a large field study in six lecture halls with 178 students. The relationship between the operative temperature and behavioral adaptations was determined. In the developed adaptive model, the acceptable indoor neutral temperatures lay within the range of 23.9-26.0 oC, with outdoor temperatures ranging between 27.0–34.6oC. The most comfortable temperature for students in the lecture hall was 25.7 oC. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hot%20and%20humid" title="hot and humid">hot and humid</a>, <a href="https://publications.waset.org/abstracts/search?q=lecture%20halls" title=" lecture halls"> lecture halls</a>, <a href="https://publications.waset.org/abstracts/search?q=neutral%20temperature" title=" neutral temperature"> neutral temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20thermal%20comfort%20model" title=" adaptive thermal comfort model"> adaptive thermal comfort model</a> </p> <a href="https://publications.waset.org/abstracts/15160/adaptive-thermal-comfort-model-for-air-conditioned-lecture-halls-in-malaysia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15160.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info 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