The need for trading off interpretability and accuracy is intrinsic to the use of fuzzy systems.
The obtaining of accurate but also human-comprehensible fuzzy systems played a key role …

Abstract System modeling with fuzzy rule-based systems (FRBSs), ie fuzzy modeling (FM),
usually comes with two contradictory requirements in the obtained model: the interpretability …

This paper proposes a genetic algorithm-based method for sizing the energy storage system
(ESS) in microgrids. The main goal of the proposed method is to find the energy and power …

Consideration is given to the preemptive scheduling of hard-real-time sporadic task systems
on one processor. The authors first give necessary and sufficient conditions for a sporadic …

Although fuzzy systems demonstrated their ability to solve different kinds of problems in
various applications, there is an increasing interest on augmenting them with learning …

Genetic Algorithm is a search heuristic that mimics the process of evaluation. Genetic
Algorithms can be applied to process controllers for their optimization using natural …

The use of genetic algorithms (GAs) and other evolutionary optimization methods to design
fuzzy rules for systems modeling and data classification have received much attention in …

Intelligence systems. We perfonn routine tasks on a daily basis, as for example:• recognition
of faces of persons (also faces not seen for many years),• identification of dangerous …

In these days, EC companies are eager to learn about their customers using data mining
technologies. But the diverse situations of such companies make it difficult to know which is …

Recently, the piecewise linear representation (PLR) method has been applied to the stock
market for pattern matching. As such, similar patterns can be retrieved from historical data …