An algorithm is presented that uses evolutionary programming to construct fuzzy membership functions that are used to extract Zadeh-Mamdani fuzzy rules from a constructive neural network. The algorithm has potential applications in fields such as data mining and knowledge-based decision support systems. Evaluation of the algorithm over two well known benchmark data sets shows that while the res...

This paper presents a new technique for multimodal image fusion. Unlike most previous works on image fusion, this paper explores the use of fuzzy lattice theory in the fusion process. Our proposed image fusion algorithm involving infrared and visual images based on fuzzy lattice theory show better experimental result than the related research work. Finally the paper discusses several key topics...

A wide variety of knowledge acquisition methods exist for conventional knowledge types such as production rule, semantic knowledge, etc. However, need for causal knowledge acquisition has not been stressed in the expert systems fields. The objectives of this paper are to (1) suggest a causal knowledge acquisition process and (2) investigate the causal knowledge-based inference process. FCM (Fuz...

Fuzzy logic controllers have gained popularity in the past few decades with highly successful implementation in many fields. Fuzzy logic enables designers to control complex systems more effectively than traditional methods. Teaching students fuzzy logic in a laboratory can be a time-consuming and an expensive task. This paper presents a low-cost educational microcontroller-based tool for fuzzy...

A new more informative and effective fuzzy discriminant analysis method based on fuzzy regression with point prototypes has been developed and applied on two relevant data sets (the classical Fisher’s Iris data set and a clinical data set concerning different diseases). The proposed fuzzy method is consistent with the supervised character of the original discriminant analysis method. The classi...

In the last thirty years fuzzy logic became very popular. One can find solutions based on it in several fields from industrial systems to house appliances. Recently a new category of fuzzy systems gained more attention, the so called fuzzy rule interpolation (FRI) based systems. Owing to the low complexity of their rule bases, i.e. they can infer as well when only the relevant rules are known, ...

As many data-driven fields, finance is rich in problems requiring high computational power and intelligent systems techniques. In particular, the problem of selecting an optimal financial portfolio can be conveniently represented as a constrained optimization problem or a decisionmaking problem. The aim of this paper is to show how to express the optimal portfolio selection problem from a decis...

The genetic algorithm has been widely used in many fields as an easy robust global search and optimization method. This paper introduces a new approach to find fuzzy rules using niche genetic algorithms with elitist migrating operator. It uses binary coding scheme. In order to make search results stable, elitist migrating operator reserves good individuals into an elitist sub-population. The si...