multi objective quadratic fractional programming (moqfp) problem involves optimization of several objective functions in the form of a ratio of numerator and denominator functions which involve both contains linear and quadratic forms with the assumption that the set of feasible solutions is a convex polyhedral with a nite number of extreme points and the denominator part of each of the object...

Nowadays, automatic learning of fuzzy rule-based systems is being addressed as a multi-objective optimization problem. A new research area of multi-objective genetic fuzzy systems (MOGFS) has capture the attention of the fuzzy community. Despite the good results obtained, most of existent MOGFS are based on a gross usage of the classic multi-objective algorithms. This paper takes an existent MO...

The aim of this paper is to propose a new method for building a fuzzy partition on multi-dimensional spaces. This method is apply for creating fuzzy symbolic sensors which use multi-component measurements. Colour sensing is an interesting perception to apply this method. Indeed, men have good control on this sensing but can not explain it simply. Then, the fuzzy colour sensor can learn human pe...

Soft computing is likely to play aprogressively important role in many applications including image enhancement. The paradigm for soft computing is the human mind. The soft computing critique has been particularly strong with fuzzy logic. The fuzzy logic is facts representationas a rule for management of uncertainty. Inthis paperthe Multi-Dimensional optimized problem is addressed by discussing...

A multi-classifier system obtained by combining several individual classifiers usually exhibits a better performance (precision) than any of the original classifiers. In this work we use a multi-classifier based on a forest of randomly generated fuzzy decision trees (Fuzzy Random Forest), and we propose a new method to combine their decisions to obtain the final decision of the forest. The prop...

A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifies numerous temporal association rules that occur more frequently in areas of a dataset with specific quantitative values represented with fuzzy sets. The novelty of this research lies in exploring the composition of qu...

In (Computing with Words, Wiley, New York, 2001, p. 251; Soft Comput. 6 (2002) 320; Fuzzy Logic and The Internet, Physica-Verlag, Springer, Wurzburg, Berlin, 2003) we presented di>erent fuzzy linguistic multi-agent models for helping users in their information gathering processes on the Web. In this paper we describe a new fuzzy linguistic multi-agent model that incorporates two information $lt...

In this paper, multi-dimensional Wiener-Liu process is proposed. Wiener-Liu process is a type of hybrid process, it corresponds to Brownian motion (Wiener process) in stochastic process and Liu process in fuzzy process. In classical analysis, the basic operations are differential and integral. Correspondingly, Ito-Liu formula plays the role of Ito formula in stochastic process and Liu formula i...

Nowadays, information gathering in Internet is a complex activity and Internet users need systems to assist them to obtain the information required. In an earlier studies [5, 6, 16] we presented different fuzzy linguistic multi-agent models for helping users in their information gathering processes on the Web. In this paper, we present a new fuzzy linguistic multi-agent model to access informat...

Genetic algorithm is one of the main heuristics that have been applied to scheduling problems in the last few decades. This paper presents a generalization of the genetic algorithm for solving project scheduling problem under time uncertainties within resource leveling technique. The generalization consists of handling fuzzy time parameter and fuzzy resource distribution instead of crisp ones. ...