The world we live in is becoming ever more reliant on the use of electronics and computers
to control the behavior of real-world resources. For example, an increasing amount of …

Abstract The term Soft Computing (SC) represents the combination of emerging problem-
solving technologies such as Fuzzy Logic (FL), Probabilistic Reasoning (PR), Neural …

This text is an introduction to Simulink, a companion application to MATLAB. It is written for
students at the undergraduate and graduate programs, as well as for the working …

Adaptive k-means clustering algorithms have been used in several artificial neural network
architectures, such as radial basis function networks or feature-map classifiers, for a …

The paper discusses relationships between conceptual and computational platforms of fuzzy
sets and neurocomputations. Fuzzy sets provide an interesting and powerful scheme of …

Soft computing (SC) is an association of computing methodologies that includes as its
principal members fuzzy logic, neurocomputing, evolutionary computing and probabilistic …

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 …

The increased popularity of hybrid intelligent systems in recent times lies to the extensive
success of these systems in many real-world complex problems. The main reason for this …

In this paper, we study the ability of learning automata-based schemes in escaping from
local minima when standard backpropagation (BP) fails to find the global minima. It is …

In common neural network practice, algorithms require heuristic rules. We introduce a better
way of using heuristics by means of a fuzzy logic controller to adjust neural network …