A Fuzzy logic system has been shown to be able to arbitrarily approximate any nonlinear function and has been successfully applied to system modelling. The functional rule fuzzy system enables the input-output relation of the fuzzy logic system to be analysed. B-spline basis functions have many desirable numerical properties and as such can be used as membership functions of fuzzy system. This ...

Neurofuzzy systems have been widely applied to a diverse range of applications because their robust operation and network transparency. A neurofuzzy system is specified by a set of rules with confidences. However, as knowledge base systems, neurofuzzy systems suffer from the curse of dimensionality i.e., exponential increase in the demand of resources and in the number of rules. So, the interpr...

Credit-risk evaluation decisions are important for the ®nancial institutions involved due to the high level of risk associated with wrong decisions. The process of making credit-risk evaluation decision is complex and unstructured. Neural networks are known to perform reasonably well compared to alternate methods for this problem. However, a drawback of using neural networks for credit-risk eva...

A neurofuzzy methodology is presented for motion planning in semi-autonomous mobile robots. The robotic automata considered are devices whose main feature is incremental learning from a human instructor. Fuzzy descriptions are used for the robot to acquire a repertoire of behaviors from an instructor which it may subsequently refine and recall using neural adaptive techniques. The robot is endo...

In this paper, an intelligent controller is applied to govern the dynamics of electrically heated micro-heat exchanger plant. First, the dynamics of the micro-heat exchanger, which acts as a nonlinear plant, is identified using a neurofuzzy network. To build the neurofuzzy model, a locally linear learning algorithm, namely, locally linear mode tree (LoLiMoT) is used. Then, an intelligent contro...

The aim of this work is to study the applications of soft computing technique on the machinability of bagasse fiber-reinforced vinyl ester composites. The prediction accuracy of regression, artificial neural networks, and neuro-fuzzy methods on the response variables during machining of bagasse fiber-reinforced vinyl ester composite sheets.. In experimental part, a total of 27 experiments was c...

This paper describes a neurofuzzy-based approach to automatically classify publicly accessible World Wide Web sites. The suggested methodology appears most relevant investigating corporate Web sites for advertising and customer support purposes but is equally valuable for analysing the hypertext structures of educational or non-profit organisations. Future efforts will focus on extending the fr...