This paper introduces a new method for fuzzy modeling based on a hierarchical fuzzy-
clustering scheme. The method consists of a sequence of steps aiming towards developing …

Let us first recall a general model of an artificial neural network that consists of s simple
computational units or neurons, indexed as V={1,..., s}, where s=| V| is called the network …

This paper introduces the Inverted Hierarchical Neuro-Fuzzy BSP System (HNFB/sup-1/), a
new neuro-fuzzy model that has been specifically created for record classification and rule …

Studies in Evolutionary Fuzzy Systems (EFSs) began in the 90s and have experienced a fast
development since then, with applications to areas such as pattern recognition, curve‐fitting …

This book introduces the novel concept of a fuzzy network. In particular, it describes further
developments of some results from its predecessor book on Complexity Management in …

The two-spiral task is a well-known benchmark for binary classification. The data consist of
points on two intertwined spirals which cannot be linearly separated. This article reviews …

Typically, Takagi–Sugeno–Kang (TSK) fuzzy rules have been used as a powerful tool for
function approximation problems, since they have the capability of explaining complex …

Over the past few years, fuzzy control FC can be designed without needing an exact
mathematical model of the system to be controlled, and can efficiently control complex …

This paper introduces a new hybrid neuro-fuzzy model, called HNFB, and evaluates its
performance in short-term load forecasting. To this end, two Brazilian electric power …

The ultimate challenges of system modeling concern designing accurate yet highly
transparent and user-centric models. We have witnessed a plethora of neurofuzzy …