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Publication: IIP Proceedings Year: 2022, Month: November Page No: 323-329, ISSN/ISBN: 978-81-959356-3-5, DOI/Link: https://rsquarel.org/assets/docupload/rsl202322BBBB681F66404.pdf
SWARM INTELLIGENCE: PSO ALGORITHM
Area/Stream: Computing Technologies and Data Sciences, Authors: S. Vishalatchi Keywords: : Nature Inspired algorithms, Swarm Intelligence(SI), Particle Swarm Optimization (PSO), PySwarms Book Name /series: Futuristic Trends in Computing Technologies and Data Sciences,Volume 2, Book 18, Part 7, Chapter 1Publication: IIP Proceedings Year: 2022, Month: November Page No: 323-329, ISSN/ISBN: 978-81-959356-3-5, DOI/Link: https://rsquarel.org/assets/docupload/rsl202322BBBB681F66404.pdf
Abstract:
A natural metaphor is a key to solve any complex optimization problem in scientific community. [1]The classical optimization problem is unable to solve the highly non linear problem because of non-adaptability. A flexible and adaptable algorithm is needed to model the real-time problem easily. More nature inspired algorithms were emerged. One of such algorithm is Swarm Intelligence (SI) that highly focuses on collective behaviour of animals and solve the problem by building a self organising system [1].[2]Most of the SI algorithms uses multiple agents to interact to the population. It uses real-number strings to solve the problem efficiently [2]. [3]Particle Swarm Intelligence(PSO) is an important searching algorithm that finds the optimum solution in an environment. This article show cases the implementation of PSO algorithm in a real time problems[3]
Cite this: S. Vishalatchi,"SWARM INTELLIGENCE: PSO ALGORITHM", Futuristic Trends in Computing Technologies and Data Sciences,Volume 2, Book 18, Part 7, Chapter 1, November, 2022, 323-329, 978-81-959356-3-5, https://rsquarel.org/assets/docupload/rsl202322BBBB681F66404.pdf
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