Training ANFIS Using Catfish-Particle Swarm Optimization for Classification

Norlida Hassan, Rozaida Ghazali, Kashif Hussain

Research output: Chapter in Book/Report/Published conference proceedingConference contributionpeer-review


ANFIS performance depends on the parameters it is trained with. Therefore, the training mechanism needs to be faster and reliable. Many have trained ANFIS parameters using GD, LSE, and metaheuristic techniques but the efficient one are still to be developed. Catfish-PSO algorithm is one of the latest successful swarm intelligence based technique which is used in this research for training ANFIS. As opposed to standard PSO, Catfish-PSO has string exploitation and exploration capability. The experimental results of training ANFIS network for classification problems show that Catfish-PSO algorithm achieved much better accuracy and satisfactory results.
Original languageEnglish
Title of host publicationRecent Advances on Soft Computing and Data Mining
Subtitle of host publicationThe Second International Conference on Soft Computing and Data Mining (SCDM-2016), Bandung, Indonesia, August 18-20, 2016 Proceedings
EditorsTutut Herawan, Rozaida Ghazali, Nazri Mohd Nawi, Mustafa Mat Deris
Number of pages10
ISBN (Electronic)978-3-319-51281-5
ISBN (Print)978-3-319-51279-2
Publication statusPublished - 29 Dec 2016

Publication series

NameAdvances in Intelligent Systems and Computing

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