The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Optimization Algorithms
Abstract
In this chapter, the basic definition of Genetic Algorithm (GA) and some of the main operations applied in GA are explained. In addition, Swarm Intelligence (SI) is briefly explained as the new branch of intelligent behavior of nature phenomena. Although PSO has been explained in past chapters, this chapter explains PSO in detail and an example of the way PSO works is provided for better understanding. Some of the differences of Particle Swarm Optimization (PSO) and GA are provided and readers will learn how to use GA and PSO for training the neural network. The experiments and contents in this chapter are from the study by Nuzly (2006) in her thesis entitled “Particle Swarm Optimization for Neural Network Learning Enhancement”.
Related Content
|
Vinod Kumar, Himanshu Prajapati, Sasikala Ponnusamy.
© 2023.
18 pages.
|
|
Sougatamoy Biswas.
© 2023.
14 pages.
|
|
Ganga Devi S. V. S..
© 2023.
10 pages.
|
|
Gotam Singh Lalotra, Ashok Sharma, Barun Kumar Bhatti, Suresh Singh.
© 2023.
15 pages.
|
|
Nimish Kumar, Himanshu Verma, Yogesh Kumar Sharma.
© 2023.
16 pages.
|
|
R. Soujanya, Ravi Mohan Sharma, Manish Manish Maheshwari, Divya Prakash Shrivastava.
© 2023.
12 pages.
|
|
Nimish Kumar, Himanshu Verma, Yogesh Kumar Sharma.
© 2023.
22 pages.
|
|
|