In genetic fuzzy systems (GFS) the size of the problem has a huge influence in the performance of the obtained models, since i) the fuzzy rule bases learned suffer from exponential rule explosion when the number of variables increases, and ii) the convergence time increments with the number of examples. In this paper we present S-FRULER, a scalable distributed version of FRULER which is a GFS t...

A Ruspini partition is a finite family of fuzzy sets {f1, . . . , fn}, fi : [0, 1] → [0, 1], such that ∑ n i=1 fi(x) = 1 for all x ∈ [0, 1]. We analyze such partitions in the language of Gödel logic. Our main result identifies the precise degree to which the Ruspini condition is expressible in this language, and yields inter alia a constructive procedure to axiomatize a given Ruspini partition ...

This paper compares a genetic programming approach with a greedy partition algorithm (LOLIMOT) for structure identi cation of local linear neuro-fuzzy models. The crisp linear conclusion part of a Takagi-Sugeno-Kang (TSK) fuzzy rule describes the underlying model in the local region speci ed in the premise. The objective of structure identi cation is to identify an optimal partition of the inpu...

In many practical applications, it is useful to represent a function f(x) by its fuzzy transform, i.e., by the “average” values Fi = ∫ f(x) ·Ai(x) dx ∫ Ai(x) dx over different elements of a fuzzy partition A1(x), . . . , An(x) (for which Ai(x) ≥ 0 and n ∑ i=1 Ai(x) = 1). It is known that when we increase the number n of the partition elements Ai(x), the resulting approximation get closer and cl...

This paper proposes a novel approach for identification of Takagi–Sugeno (T–S) fuzzy model, which is based on a new fuzzy c-regression model (FCRM) clustering algorithm. The clustering prototype in fuzzy space partition is hyper-plane, so FCRM clustering technique is more suitable to be applied in premise parameters identification of T–S fuzzy model. A new FCRM clustering algorithm (NFCRMA) is ...

In Power efficient routing for MANET is very crucial due to its dynamic topology, complexity and limited resources. The battery efficiency and power consumption of the selected routes play a vital role in the network lifetime. An optimum balance between these two constraints has to be made during route selection in order to obtain stable routes that would avoid network partitioning. In this pap...

In evidential clustering, uncertainty about the assignment of objects to clusters is represented by Dempster-Shafer mass functions. The resulting clustering structure, called a credal partition, is shown to be more general than hard, fuzzy, possibilistic and rough partitions, which are recovered as special cases. Three algorithms to generate a credal partition are reviewed. Each of these algori...