Particle Swarm Optimization Algorithm(MATLAB Implementation)

Particle Swarm Optimization Algorithm(MATLAB Implementation), available at $54.99, has an average rating of 4.6, with 24 lectures, based on 167 reviews, and has 1503 subscribers.

You will learn about 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 This course is ideal for individuals who are Undergraduate, Post graduate Students and PhD scholars of all Engineering disciplines It is particularly useful for Undergraduate, Post graduate Students and PhD scholars of all Engineering disciplines.

Enroll now: Particle Swarm Optimization Algorithm(MATLAB Implementation)

Summary

Title: Particle Swarm Optimization Algorithm(MATLAB Implementation)

Price: $54.99

Average Rating: 4.6

Number of Lectures: 24

Number of Published Lectures: 24

Number of Curriculum Items: 24

Number of Published Curriculum Objects: 24

Original Price: $19.99

Quality Status: approved

Status: Live

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

Who Should Attend

Undergraduate, Post graduate Students and PhD scholars of all Engineering disciplines

Target Audiences

Undergraduate, Post graduate Students and PhD scholars of all Engineering disciplines

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

Course Curriculum

Chapter 1: Basics of MATLAB programming

Lecture 1: Introduction

Lecture 2: Variables and Operators

Lecture 3: Vector Declaration

Lecture 4: indexing and Size of Vector

Lecture 5: Matrix Operations

Lecture 6: max(), min(), ones() and zeros()

Lecture 7: rand(), randi() and repmat()

Lecture 8: If Statement

Lecture 9: For Loop

Lecture 10: While Loop

Lecture 11: Functions

Lecture 12: Plots

Chapter 2: Concept of Optimization and Particle Swarm Optimization (PSO)

Lecture 1: Introduction to Optimization

Lecture 2: Effect of Constraints on Optimal Solution

Lecture 3: Terminologies Used in Optimization and Pseudo Codes

Lecture 4: Philosophy of PSO algorithm- Part I

Lecture 5: Philosophy of PSO algorithm- Part II

Chapter 3: MATLAB Implementation of PSO algorithm to solve benchmark functions

Lecture 1: Matyas Function Introduction

Lecture 2: Matyas Function Coding Part I

Lecture 3: Matyas Function Coding Part II

Lecture 4: Rosenbrock Function Introduction

Lecture 5: Rosenbrock Function Coding

Chapter 4: Project

Lecture 1: Project Problem Introduction

Lecture 2: Project Problem Coding

Instructors

Mayank Dadge
B.Tech Mechanical Engineering
Dr. H. T. Jadhav
B.E. (Power Engg.), M.Tech (Power Engg.), Ph.D.(Power Engg.)

Rating Distribution

1 stars: 2 votes
2 stars: 2 votes
3 stars: 7 votes
4 stars: 36 votes
5 stars: 120 votes

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