Particle Swarm Optimization

By James Kennedy. Encyclopedia of Machine Learning and Data Mining, 2010

399 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/246d317528c9d0c88721835fb2ecface139f62bf

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Citations in the corpus

Application of soft computing techniques in machining performance prediction and optimization: a literature review (2010, unknown): “Particle swarm optimization is a population-based stochastic optimization technique developed by Kennedy and Eberhart in 1995 and is inspired by the social behavior of bird flocking or fish schooling [15].”
Butterfly optimization algorithm: a novel approach for global optimization (2018, methodology): “The algorithm combines both the learning phenomenon leading the solu-tion to evolve in a better way as the algorithm proceeds (Kennedy 2010).”
Evolutionary Techniques for Model Order Reduction of Large Scale Linear Systems (2009, unknown): “The objective is to find a reduced thr order reduced model )(sR such that it retains the important properties of )(sG for the same types of inputs.”
Benchmark Functions for the CEC'2013 Special Session and Competition on Large-Scale Global Optimization (2008, unknown): “1 Introduction Numerous metaheuristic algorithms have been successfully applied to many optimization problems [1, 2, 5, 9, 10, 15, 16, 17, 21, 35, 39].”
COVID-19 Outbreak Prediction with Machine Learning (2020, background): “All of these features make PSO different from the GA and other innovative algorithms [61,65,67].”
A Generic and Robust System for Automated Patient-Specific Classification of ECG Signals (2009, unknown): “The PSO was introduced by Kennedy and Eberhart in 1995 as a population-based stochastic search and optimization process [ 30 ].”