Application of the Intuitionistic Fuzzy InterCriteria Analysis Method to a Neural Network Preprocessing Procedure

Abstract

The artificial neural networks (ANN) are a tool that can be used for object recognition and identification.However, there are certain limits when we may use ANN, and the number of the neurons is one of the major parameters during the implementation of the ANN.On the other hand, the bigger number of neurons slows down the learning process.In our paper, we propose a method for removing the number of the neurons without reducing the error between the target value and the real value obtained on the output of the ANN's exit.The method uses the recently proposed approach of InterCriteria Analysis, based on index matrices and intuitionistic fuzzy sets, which aims to detect possible correlations between pairs of criteria.

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