GNRCS: Hybrid Classification System based on Neutrosophic Logic and Genetic Algorithm

Abstract

In this paper, we present a hybrid intelligent system based on Neutrosophic Logic (NL). In conjunction with Genetic Algorithm(GA) for classification. The neutrosophic logic is adapted for representing different forms of knowledge. GA is used to refine the generated neutrosophic rules. The performance of the proposed system is tested on three real-world databases Iris, Wine, and Wisconsin Diagnostic Breast Cancer (WDBC). In a series of experiments, we compare the performance of the proposed genetic neutrosophic rule-based classification system with that of the neutrosophic rule-based classification system. The performance of both classifiers is measured for the three real-world data sets. We have reached an average accuracy 98.39% in genetic neutrosophic against 94.78% for the corresponding neutrosophic.