Application of Fuzzy Neural Networks Systems in Chemistry

APPLICATION OF FUZZY NEURAL NETWORKS SYSTEMS IN CHEMISTRY 

The artificial neural networks, mentioned above, represent a multitude of parallel structures consisting of nonlinear processing units connected by 

Within the field of chemistry, various applications have already been published. Jansson and Zupan and Gasteiger published an overview of an MLP (multilayer perceptron), that is trained by back-propagation of errors, and other types of neural networks. However, the basic source in this field continues to be the well-known book of Zupan and Gasteiger. In analytical chemistry, neural networks have been applied to pattern recognition, modeling, and prediction, for example, in multicomponent analysis or process control, to classification, clustering and pattern association. 

It is abundantly clear that fuzzy logic is better able to represent human knowledge in a form of rules while ANNs are better able to learn from examples. As a consequence of their complementary properties, then, extensive efforts are being made to combine fuzzy theory and neutral networks to profit from the advantages of each while trying to bypass the disadvantages of the isolated techniques. 

A fuzzy multivariate rule-building expert system (FuRES) has been devised that also functions as a minimal neural network. This system builds 

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Application of Fuzzy Neural Networks Systems in Chemistry 323... 

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