Particle Swarm Optimization for Beginners

Particle Swarm Optimization
Free tutorial
Rating: 3.9 out of 5 (23 ratings)
551 students
1hr 17min of on-demand video

Basics of Particle Swarm Optimization


  • Basic Mathematics


Collective intelligence in nature through collective behaviors is observed in swarm of bees colony of ants, flock of birds, school of fish and herd of animals. Collective intelligence through Social interaction in a group can provide a solution to a cognitive problem. Swarm intelligence is observed.

New computing techniques are developed by observing how naturally occurring phenomena behave to solve complex problems. Bio-inspired computing represents the umbrella of different studies of computer science, mathematics, and biology. Bio-inspired computing optimization algorithms is an emerging approach which is based on the principles and inspiration of the biological evolution of nature to develop new and robust competing techniques.

Particle Swarm Optimization (PSO) is metaheuristic algorithm. It is inspired by collective intelligence.

The course covers introductory topics in swarm intelligence and particle swarm optimization in particular. The course covers basic variants and applications of Particle Swarm Optimization

Topics which will be discussed in this course are listed here -

1. Introduction to the course

2. Learning from Nature

3. Natural Swarm

4. Swarm behavior

5. Collective Intelligence I

6. Collective Intelligence II

7. Bio Inspired Algorithms

8. Components of Optimization

9. Classification of Optimization Problem

10. Swarm Optimization

11. Boid : Bird Flocking

12. Particle Swarm Optimization : Introduction I

13. Particle Swarm Optimization : Introduction II

14. Particle Swarm Optimization Algorithm Variants

15. Particle Swarm Optimization : Applications

Who this course is for:

  • Particle Swarm Optimization beginners


Snehal Kamalapur
  • 3.9 Instructor Rating
  • 23 Reviews
  • 551 Students
  • 1 Course

Snehal Kamalapur is PhD in Computer Engineering. She is passionate about teaching.  Currently she is working as professor.  Her research interest are in the areas of Artificial Intelligence, Machine learning and data science. Over the last 23 years, she has  acquired valuable skills and experience. She is passionate about teaching skills that may provide great learning experience.

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