Computational Intelligence comprises concepts, paradigms, algorithms, and
implementations of systems that are supposed to exhibit intelligent behavior in complex …

While I have long been an admirer of Kosko's research (including bidirectional associative
memory, fuzzy associative memory, and fuzzy cognitive maps), I have not found his …

In recent years, a great number of publications have explored the use of genetic algorithms
as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this …

Fuzzy rule-based systems (FRBSs) are a well-known method family within soft computing.
They are based on fuzzy concepts to address complex real-world problems. We present the …

Many approaches have already been proposed for classification and modeling in the
literature. These approaches are usually based on mathematical mod els. Computer …

Recent advances in the information and communication technologies are leading to an
exponential growth in the amount of data stored in databases. It has been estimated that this …

The integration of neural networks and fuzzy inference systems could be formulated into
three main categories: cooperative, concurrent and integrated neuro-fuzzy models. We …

Most fuzzy controllers and fuzzy expert systems must predefine membership functions and
fuzzy inference rules to map numeric data into linguistic variable terms and to make fuzzy …

Conventional model-based data processing methods are computationally expensive and
require experts' knowledge for the modelling of a system. Neural networks are a model-free …

Finding information hidden in data is as theoretically difficult as it is practically important.
With the objective of discovering unknown patterns from data, the methodologies of data …