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Solving Uncertain Problems using ANFIS

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Author(s): Dr G.S.V.P. Raju | V. Mary Sumalatha | K.V. Ramani | K.V. Lakshmi

Journal: International Journal of Computer Applications
ISSN 0975-8887

Volume: 29;
Issue: 11;
Start page: 14;
Date: 2011;
Original page

Keywords: Soft Computing | Hybrid Intelligent | Systems Robustness | Neuro-Fuzzy model | ANFIS

ABSTRACT
Uncertain problems are problems that have no definitive way of solving. Many of the uncertain problems come under intelligence systems that exhibit the characteristics we associate with intelligence in human behavior. Soft Computing[6] techniques which have drawn their inherent characteristics from biological systems, present an effective method for solving of even difficult inverse problems. The guiding principle of soft computing is to exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low cost solution, employment of soft computing for the solution of machine learning problems lead to high machine intelligence quotient. Hybrid intelligent systems deal with the integration of two or more of the technologies. The combined use of technologies has resulted in effective problem solving in comparison with each technology used individually and exclusively. The purpose of the paper is to solve an engineering problem, power failures in personal computers using neuro fuzzy modeling system ANFIS.
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