A way to automatically generate fuzzy controllers (FCs) that are optimized according to a merit figure is presented in this article. To achieve this task, a procedure based on hierarchical genetic algorithms (HGA) was developed. This procedure and the manner in which fuzzy controllers are codified into chromosomes is described. Resorting to this tool, several fuzzy controllers were constructed....

The performance of commercial websites is a critical issue that has a significant effect on consumers’ online decision-making. This study develops and applies a fuzzy model to assess the performance of hotel websites. It presents a fuzzy decision-making approach to the evaluation of tourism website performance that integrates consumer perceptions with a hierarchical model. The model consists of...

Purpose International collaboration is a crucial requirement of entrepreneurship, particularly in developing emerging economies. This seems so necessary the food industry as major contributor to environmental, social and economic problems. paper aims identify, analyse influential network relationship prioritise key success factors (KSFs) international formation entrepreneurial with case study o...

Over the last years, a number of methods have been proposed to automatically learn and optimize fuzzy rule bases from data. The obtained rule bases are usually robust and allow an interpretation even for data sets that contains imprecise or uncertain information. However, most of the proposed methods are still restricted to learn and/or optimize single layer feed-forward rule bases. The main di...

Most of the technological systems are characterized by complexity, coupled relationships with feedback and a demanding procedure to develop their models. This paper presents the Soft Computing technique of Fuzzy Cognitive Maps that are knowledge-based methodologies suitable to describe and model complex systems and handle with available information from an abstract point of view. Fuzzy cognitiv...

Moved by the need increased for modeling of the fuzzy data, the success of the systems of exact generation of summary of data, we propose in this paper, a new approach of generation of summary from fuzzy data called “FuzzySaintEtiQ”. This approach is an extension of the SaintEtiQ model to support the fuzzy data. It presents the following optimizations such as 1) the minimization of the expert r...

Conventional clustering means classifying the given data objects as exclusive subsets (clusters).That means we can discriminate clearly whether an object belongs to a cluster or not. However such a partition is insufficient to represent many real situations. Therefore a fuzzy clustering method is offered to construct clusters with uncertain boundaries and allows that one object belongs to overl...

In the recent years, a high number of fuzzy rule learning algorithms have been developed with the aim of building the Knowledge Base of Linguistic Fuzzy Rule Based Systems. In this context, it emerges the necessity of managing a flexible structure of the Knowledge Base with the aim of modeling the problems with a higher precision. In this work, we present a short overview on the Hierarchical Fu...