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1
Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…Clustering, an unsupervised method of grouping sets of data, is used as a solution technique in various fields to divide and restructure data to become more significant and transform them into more useful information. …”
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2
Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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3
Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm
Published 2023“…One of the search methods commonly used to find solutions for the trade-off problem in various fields is the Multi-Objective Evolutionary Algorithm (MOEA). …”
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Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis
Published 2019“…In addition, such hybridization get the solutions achieved are well spread over it. As a result of using a local search method the quality of the Pareto optimal solutions are increased and all individuals in the population are enhanced. …”
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5
Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm
Published 2023“…In any metaheuristic, the parameter values strongly affect the efficiency of an algorithm’s search. This research aims to find the optimal parameter values for the Pareto Ant Colony System (PACS) algorithm, which is used to obtain solutions for the generator maintenance scheduling problem. …”
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6
Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems
Published 2015“…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems
Published 2015“…The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions. …”
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Enhanced algorithms for three-dimensional object interpreter
Published 2004“…Besides reducing the number of image regularities used and new method to solve the linear system, this study has proposed better solutions in terms of an enhanced thinning algorithm, a modified Freeman chain code algorithm as picture description language, and a new computational comer detection algorithm.…”
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Thesis -
9
Tag clouds algorithm with the inclusion of personality traits
Published 2015“…This algorithm is beneficial for decision making using information visualization in which personality traits of the user are heavily inclined. …”
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Vehicle detection for vision-based intelligent transportation systems using convolutional neural network algorithm
Published 2022“…Software based solutions using traditional algorithms such as Histogram of Gradients (HOG) and Gaussian Mixed Model (GMM) are computationally slow and not suitable for real-time traffic detection. )erefore, the paper will review and evaluate different vehicle detection methods. …”
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Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language
Published 2019“…CT is not merely using software or computer programs alone but is also interlinked with information and communication technology (ICT) and computer science based on problems; tools; action (praxis); solutions; concepts; and social needs. …”
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12
Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Meta-heuristic algorithms are search techniques used to solve complexoptimization problems, and these algorithms can help provide reasonable solutions in a shorter time thanexact methods. …”
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Application of induced preorderings in score function-based method for solving decision-making with interval-valued fuzzy soft information
Published 2021“…Then, using the preorder relation on a topological space, a score function-based ranking system is also defined to design an adjustable multi-steps algorithm. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…This indicates the capability of the algorithm in exploring the search space. The 2S-ENDSHHMO algorithm can be used to improve the search process of other MOSI-based algorithms and can be applied to solve MOPs in applications such as structural design and signal processing.…”
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15
Algorithm as a problem solving technique for teaching and learning of the Malay language
Published 2019“…CT is not merely using software or computer programs alone but is also interlinked with information and communication technology (ICT) and computer science based on problems; tools; action (praxis); solutions; concepts; and social needs. …”
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Local Search Based Enhanced Multi-objective Genetic Algorithm of Training Backpropagation Neural Network for Breast Cancer Diagnosis
Published 2017“…Most of multi-objective evolutionary algorithms used NSGA-II due to a good performance in comparison with other multi-objective evolutionary algorithms. …”
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Book Chapter -
17
Semantic relatedness maximisation for word sense disambiguation using a hybrid firefly algorithm
Published 2021“…This is achieved by proposing a swarm intelligence method, called firefly algorithm (FA) to find the best possible set of senses. …”
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Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification
Published 2024“…In addition, the local optima issue is overcome by the population reinitialisation method. The proposed algorithm, named the CFS-Mutable Composite Firefly Algorithm (CFS-MCFA), is evaluated based on two metrics, namely classification accuracy and genes subset size, using a Support Vector Machine (SVM) classifier. …”
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The compact genetic algorithm for likelihood estimator of first order moving average model
Published 2012“…Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. …”
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Conference or Workshop Item -
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Performance analysis of clustering based genetic algorithm
Published 2016“…The proposed CGA on which the performance analysis of this paper is based involve the use of two centroids based clustering technique as a new method of chromosomes selection at the reproduction stage in a typical Genetic Algorithm. …”
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Proceeding Paper
