Particle Swarm Optimization in MATLAB – Free Udemy Courses
A video tutorial on PSO and its implementation in MATLAB from scratch
What you’ll learn
Particle Swarm Optimization in MATLAB – Free Udemy Courses
- Understand what is Particle Swarm Optimization (PSO) and how it works
- Implement PSO in MATLAB from scratch
- Improve the PSO using Constriction Coefficients
- Solve optimization problems using PSO
Requirements
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Optimization, especially intelligent optimization tools
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MATLAB programming
Description
Particle Swarm Optimization (PSO)
is an intelligent optimization algorithm based on Swarm Intelligence. It is based on a simple mathematical model, developed by Kennedy and Eberhart in 1995, to describe the social behavior of birds and fish. The model relies mostly on the basic principles of self-organization which is used to describe the dynamics of complex systems. PSO utilizes a very simplified model of social behavior to solve optimization problems, in a cooperative and intelligent framework. PSO is one of the most useful and famous metaheuristics and it is successfully applied to various optimization problems.
The instructor of this course is
Dr. S. Mostapha Kalami Heris
, Control and Systems Engineering Ph.D. and member of the Yarpiz Team.
After watching this video tutorial, you will be able to know what is PSO, how it works, and how you can use it to solve your optimization problems. Also, you will learn how to implement PSO in MATLAB programming language. If you are familiar with other programming languages, it is easy to translate the MATLAB code and rewrite the PSO code in those languages.
Who this course is for:
- Students working on optimization problems and methods, especially engineering and science students can use PSO as an optimization tool; so this course can help them to enhance their knowledge about one of the most useful meta-heuristics.
- Anyone interested in artificial and computational intelligence will find this course useful.
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