Fuzzy systems evaluation: The inference error approach

Fuzzy systems evaluation: The inference error approach

An inference method based on an equation image of a rule-base and the minimization of a cost index (inference error) is presented. The method has several advantages: it has intuitive insight, allows more powerful rules, and also presents an interesting algebraic (minimum distance) and functional (subsethood) formulation of the meaning of inference. Analysis of internal quality and completeness ...

the use of appropriate madm model for ranking the vendors of mci equipments using fuzzy approach

abstract nowadays, the science of decision making has been paid to more attention due to the complexity of the problems of suppliers selection. as known, one of the efficient tools in economic and human resources development is the extension of communication networks in developing countries. so, the proper selection of suppliers of tc equipments is of concern very much. in this study, a ...

Fuzzy Inference Systems Optimization

This paper compares various optimization methods for fuzzy inference system optimization. The optimization methods compared are genetic algorithm, particle swarm optimization and simulated annealing. When these techniques were implemented it was observed that the performance of each technique within the fuzzy inference system classification was context dependent.

An Evaluation of the Systems Reliability Using Fuzzy Lifetime Distribution

Neural Networks, Fuzzy Inference Systems and Adaptive-Neuro Fuzzy Inference Systems for Financial Decision Making

This paper employs pattern classification methods for assisting investors in making financial decisions. Specifically, the problem entails the categorization of investment recommendations. Based on the forecasted performance of certain indices, the Stock Quantity Selection Component is to recommend to the investor to purchase stocks, hold the current investment position or sell stocks in posses...