From the Publisher: Fuzzy and Neural Approaches in Engineering presents a detailed
examination of the fundamentals of fuzzy systems and neural networks and then joins them …

1995. Fuzzy sets were introduced by Zadeh (1965) as a means of representing and
manipulating data that was not precise, but rather fuzzy. Fuzzy logic provides an inference …

Fuzzy sets were introduced by Zadeh (1965) as a means of representing and manipulating
data that was not precise, but rather fuzzy. Fuzzy logic pro vides an inference morphology …

The concepts of fuzzy set and of its applications has become a battlefield of conflicting
opinions, since its steady development during the sixties. On the one hand, in the camp of …

The emerging need for Hybrid Intelligent Systems (HIS) is currently motivating important
research and development work. The integration of different learning and adaptation …

An architecture for neural networks that can handle fuzzy input vectors is proposed, and
learning algorithms that utilize fuzzy if-then rules as well as numerical data in neural network …

Although much research has been done over the decades on the formulation of statistical
regression models for road traffic relationships, they have been largely unsuitable due to the …

We present an efficient method for selecting important input variables when building a fuzzy
model from data. Past methods for input variable selection require generating different …

This handbook provides information about fundamental aspects of the field and explores the
myriad applications of fuzzy logic techniques and methods. It presents basic conceptual …

This paper proposes an efficient fuzzy partition method of a pattern space for classification
problems. The proposed method is based on the sequential subdivision of fuzzy subspaces …