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Particle Swarm Optimization Algorithm(MATLAB Implementation)
Solving Engineering Optimization Problems using Particle Swarm Optimization algorithm (MATLAB Implementation)

This Course Includes
udemy
5 (176 reviews )
2h 59m
english
Online - Self Paced
professional certificate
Udemy
About Particle Swarm Optimization Algorithm(MATLAB Implementation)
This course is specifically developed for B. Tech. and M. Tech/MS students of all Engineering disciplines. Engineering students from all branches can take this course and apply the knowledge to solve optimization problems in their field as part of a mini-project or capstone project. In addition to this, the course is also useful to Ph. D. students of different engineering branches. This course can be taken by everyone irrespective of their programming knowledge. The basics of MATLAB programming is taught in the beginning of the course and the concept of optimization algorithms is also explained from the scratch. The content is so organized that the learner should be able to understand Engineering optimization from scratch and solve research problems leading to publication in an international journal of high repute. A guided project is also included at the end of the course to make sure students can apply the knowledge to real engineering optimization problems. It should be useful to students of all universities around the world. This course is divided into FOUR Parts
Part I - Basics of MATLAB Programming
Part 2 - Concept of Optimization and Particle Swarm Optimization (PSO) algorithm
Part 3 - MATLAB Implementation of PSO algorithm to solve benchmark functions
Part 4 - MATLAB Implementation of PSO Algorithm to solve a typical Engineering optimization Problem
What You Will Learn?
- Learn the basics of MATLAB programming .
- Understand Particle Swarm Optimization (PSO) algorithm .
- Implement PSO algorithm in MATLAB to solve benchmark functions .
- Implement PSO algorithm to solve a mechanical engineering optimization problem .
- Work on a research problem in the field of optimization.