Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy Controllers

Comparative Study of Type-2 Fuzzy Particle Swarm, Bee Colony and Bat Algorithms in Optimization of Fuzzy Controllers

In this paper, a comparison among Particle swarm optimization (PSO), Bee Colony Optimization (BCO) and the Bat Algorithm (BA) is presented. In addition, a modification to the main parameters of each algorithm through an interval type-2 fuzzy logic system is presented. The main aim of using interval...

Full description

Bibliographic Details
Main Authors: Frumen Olivas, Leticia Amador-Angulo, Jonathan Perez, Camilo Caraveo, Fevrier Valdez, Oscar Castillo
Format: Article
Language:English
Published: MDPI AG 2017-08-01
Series:Algorithms
Subjects:
interval type-2 fuzzy logic
footprint uncertainty
bio-inspired algorithms
fuzzy controller
Online Access:https://www.mdpi.com/1999-4893/10/3/101

Internet

https://www.mdpi.com/1999-4893/10/3/101

Similar Items