International Journal of Soft Computing

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A Hybrid Particle Swarm Optimization and Fuzzy Rule-Based System for Breast Cancer Diagnosis

Najmeh Alikar, Salwani Abdullah, Seyed Mohsen Mousavi and Seyed Taghi Akhavan Niaki
Page: 126-133 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

A hybrid algorithm of a particle swarm optimization and a fuzzy rule-based classification system is proposed in this study to diagnose breast cancer. Two orthogonal and triangular types of fuzzy sets are applied to represent the input variables. In additional, different input membership functions are considered to increase the classification accuracy. The performance of the proposed hybrid algorithm is studied using a classification accuracy measure on the Wisconsin breast cancer dataset. The results of the comparison using different training data sets show the higher performance of the proposed methodology.

How to cite this article:

Najmeh Alikar, Salwani Abdullah, Seyed Mohsen Mousavi and Seyed Taghi Akhavan Niaki. A Hybrid Particle Swarm Optimization and Fuzzy Rule-Based System for Breast Cancer Diagnosis.
DOI: https://doi.org/10.36478/ijscomp.2013.126.133
URL: https://www.makhillpublications.co/view-article/1816-9503/ijscomp.2013.126.133