Brain Storm Optimization Algorithms Brain Storm Optimization Algorithms
Adaptation, Learning, and Optimization

Brain Storm Optimization Algorithms

Concepts, Principles and Applications

    • € 87,99
    • € 87,99

Beschrijving uitgever

Brain Storm Optimization (BSO) algorithms are a new kind of swarm intelligence method, which is based on the collective behavior of human beings, i.e., on the brainstorming process. Since the introduction of BSO algorithms in 2011, many studies on them have been conducted. They not only offer an optimization method, but could also be viewed as a framework of optimization techniques. The process employed in the algorithms could be simplified as a framework with two basic operations: the converging operation and the diverging operation. A “good enough” optimum could be obtained through recursive solution divergence and convergence. The resulting optimization algorithm would naturally have the capability of both convergence and divergence.
This book is primarily intended for researchers, engineers, and graduate students with an interest in BSO algorithms and their applications. The chapters cover various aspects of BSO algorithms, and collectively provide broad insights into what these algorithms have to offer. The book is ideally suited as a graduate-level textbook, whereby students may be tasked with the study of the rich variants of BSO algorithms that involves a hands-on implementation to demonstrate the utility and applicability of BSO algorithms in solving optimization problems.    

GENRE
Computers en internet
UITGEGEVEN
2019
3 juni
TAAL
EN
Engels
LENGTE
314
Pagina's
UITGEVER
Springer International Publishing
GROOTTE
18,4
MB

Andere boeken in deze serie

Genetic Programming for Image Classification Genetic Programming for Image Classification
2021
Optinformatics in Evolutionary Learning and Optimization Optinformatics in Evolutionary Learning and Optimization
2021
Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling
2021
Federated and Transfer Learning Federated and Transfer Learning
2022
Adaptive Differential Evolution Adaptive Differential Evolution
2009
Computational Intelligence in Expensive Optimization Problems Computational Intelligence in Expensive Optimization Problems
2010