Volume : VIII, Issue : V, May - 2019

Optimizing Fuzzy Systems Using Evolutionary Algorithms

Kuldeep Kumar Katiyar

Abstract :

Fuzzy rule–based systems (FRBSs) are a well–known method family within soft computing.They are based on fuzzy concepts to address complex real–world problems. We present the R package frbs which implements the most widely used FRBS models, namely,Mamdani and Takagi Sugeno Kang (TSK) ones, as well as some common variants. In addition a host of learning methods for FRBSs, where the models are constructed from data,are implemented. In this way, accurate and interpretable systems can be built for data analysis and modeling tasks. In this paper, we also provide some examples on the usage of the common classification and regression methods available in R

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Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

OPTIMIZING FUZZY SYSTEMS USING EVOLUTIONARY ALGORITHMS, Kuldeep Kumar Katiyar INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH : Volume-8 | Issue-5 | May-2019

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