Search Results - (( evolution optimization clustering algorithm ) OR ( evolution classification methods algorithm ))
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1
Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…Nature-inspired optimization-based clustering techniques are powerful, robust and more sophisticated than the conventional clustering methods due to their stochastic and heuristic characteristics. …”
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2
A novel clustering based genetic algorithm for route optimization
Published 2016“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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4
Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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5
Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…The optimal results obtained for constrained engineering problems as well as data clustering are very promising in terms of quality of solutions and convergence speed of the algorithm.…”
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6
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The third method is the hybridization of BPSO and Binary Differential Evolution, namely Binary Particle Swarm Optimization Differential Evolution (BPSODE). …”
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7
Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network
Published 2019“…Further evolution of the ELEC routing protocol is presented to evaluate the impact of incremental cluster iv heads on the performance of WSN. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution
Published 2017“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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10
Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…This study is an attempt to design a method for an autonomous pattern classification and recognition system for emotion recognition. …”
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A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection
Published 2019“…To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…Autonomous manufacturing allows the system to distinguish between a mild, normal and total failure in tool condition. K-means clustering has become the most applied algorithm in discovering classes in an unsupervised scenario. …”
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Email spam classification based on deep learning methods: A review
Published 2025“…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. A thorough literature evaluation is required to have a comprehensive overview of the current research on utilizing deep learning methods for email spam classification. …”
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Artificial fish swarm optimization for multilayer network learning in classification problems
Published 2012“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems
Published 2012“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN. …”
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An adaptive HMM based approach for improving e-Learning methods
Published 2023“…This adaptive algorithm can thus be applied to any e-learning platform for optimal content delivery to its users in real-time. © 2014 IEEE.…”
Conference Paper -
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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18
Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
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Proceeding Paper -
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EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization
Published 2019“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems
Published 2021“…Such approach is highly dependable on the clustering algorithm parameterization, and is not capable to deal with the normal system’s specification changes. …”
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