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Optimization of Rules in Neuro-Fuzzy Inference Systems

Publication Type : Conference Proceedings

Publisher : International Conference on Computational Vision and Bio-inspired Computing

Source : International Conference on Computational Vision and Bio-inspired Computing (ICCVBIC 2017). Inventive Research Organization and RVS Technical Campus, Coimbatore, 2017.

Campus : Bengaluru

School : Department of Computer Science and Engineering, School of Engineering

Department : Computer Science

Year : 2017

Abstract : Optimization of rule based system with Neuro Fuzzy Inference system results better regarding accuracy and interpretability. Dynamic Evolving Neuro Fuzzy Systems (DENFIS) model is used to find out an optimized rule base using computational intelligence techniques for a target search application. The process of optimization starts at the beginning of the target search process by selecting an appropriate selection of rule based Fuzzy Inference System. Further, optimization has been addressed in the choice of the number of rules by reducing the number of attributes used in the input. The integrated approach of input selection and rule selection results in accurate target predictions. The ability of knowledge-representation, highly interpretable if…then rules and imprecision tolerance are the major features of the proposed model.

Cite this Research Publication : Amudha J. and Radha D., “Optimization of Rules in Neuro-Fuzzy Inference Systems”, International Conference on Computational Vision and Bio-inspired Computing (ICCVBIC 2017). Inventive Research Organization and RVS Technical Campus, Coimbatore, 2017.

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