Statistical Analysis of Type-1 and Interval Type-2 Fuzzy Logic in dynamic parameter adaptation of the BCO
Authors
Leticia Amador-Angulo, Oscar Castillo
Corresponding Author
Leticia Amador-Angulo
Available Online June 2015.
- DOI
- 10.2991/ifsa-eusflat-15.2015.110How to use a DOI?
- Keywords
- Adjust dynamic, bee colony optimization, fuzzy logic, uncertainty, fuzzy controller, bees.
- Abstract
A statistical analysis of Type-1 and Interval Type-2 Fuzzy Logic in dynamic parameter adaptation in the Bee Colony Optimization algorithm (BCO) is presented in this paper. The Bee Colony Optimization meta-heuristic belongs to the class of Nature-Inspired Algorithms. The objective of the work is based on the main reasons for the analysis of the approach with Interval Type-2 Fuzzy Logic to find the best parameters of the Beta and Alpha in BCO. We implemented the BCO specifically for tuning membership functions of the fuzzy controller for the benchmark problem, known as the temperature controller.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Leticia Amador-Angulo AU - Oscar Castillo PY - 2015/06 DA - 2015/06 TI - Statistical Analysis of Type-1 and Interval Type-2 Fuzzy Logic in dynamic parameter adaptation of the BCO BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 776 EP - 783 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.110 DO - 10.2991/ifsa-eusflat-15.2015.110 ID - Amador-Angulo2015/06 ER -