The learning of a Fuzzy Rule-Based Classification System (FRBCS) by means of a supervised inductive process fundamentally implies four tasks that are complementary among them: the selection of the most informative variables to the classification problem to solve, the generation of a set of rules, the selection of the subset of rules with the best co-operation and the least redundancy, and the e...

suppose $g$ is a finite group, $a$ and $b$ are conjugacy classes of $g$ and $eta(ab)$ denotes the number of conjugacy classes contained in $ab$. the set of all $eta(ab)$ such that $a, b$ run over conjugacy classes of $g$ is denoted by $eta(g)$.the aim of this paper is to compute $eta(g)$, $g in { d_{2n}, t_{4n}, u_{6n}, v_{8n}, sd_{8n}}$ or $g$ is a decomposable group of order $2pq$, a group of...

Ab.llrtI(·I: Algorithm, based 011 minimIsation of fuzzy compactness are developed whereby it is possible to obtain automatically both fuzzy and nonfu77y skeletons of an image. Compactness measure lakes into account the fuzziness In geometry of regions in an image. The memberstlip plane representing the subset 'Core line' is made gray level and position dependent sueb thai its value decreases as...

Mostly 5 to 15% of the women in the stage of reproduction face the disease called Polycystic Ovarian Syndrome (PCOS) which is the multifaceted, heterogeneous and complex. The long term consequences diseases like endometrial hyperplasia, type 2 diabetes mellitus and coronary disease are caused by the polycystic ovaries, chronic anovulation and hyperandrogenism are characterized with the resistan...

Recently there has been significant growth in research interest in type-2 fuzzy logic. Type-2 fuzzy logic is extension of type-1 (regular) fuzzy logic where the membership grade in a fuzzy set is itself measured as a fuzzy number. Much of this growth has only been concerned with type-2 interval fuzzy systems, a subset of type-2 fuzzy systems, where the membership grade of a fuzzy set is given a...

Keywords: Cluster analysis Maximum entropy principle k-means Fuzzy c-means Sample weights Robustness a b s t r a c t Although there have been many researches on cluster analysis considering feature (or variable) weights, little effort has been made regarding sample weights in clustering. In practice, not every sample in a data set has the same importance in cluster analysis. Therefore, it is in...

Considering vast and miscellaneous contents in P2P system, intelligent P2P network topology is required to route queries to a relevant subset of peers. Based on the incremental clustering capability of Fuzzy Adaptive Resonance Theory (Fuzzy ART), this paper made use of the modified fuzzy ART to provide small-world P2P construction mechanism, which was not only to categorize peers so that all th...

A subset S of V is called a dominating set in G if every vertex in V-S is adjacent to at least one vertex in S. A Dominating set is said to be Fuzzy Double Dominating set if every vertex in V-S is adjacent to at least two vertices in S. The minimum cardinality taken over all, the minimal double dominating set is called Fuzzy Double Domination Number and is denoted by γ fdd (G). The minimum numb...

Fuzzy inclusion dependencies ( , [0, FID s α 1]) α ∈ express subset-relationships between fuzzy databases and are thus important indicators for redundancies between fuzzy databases. In general, the discovery of FID s α will be beneficial in any effort to integrate unknown fuzzy databases. The problem of searching FID s α between two fuzzy relations is NP-hard. Therefore, we have mapped the FID ...

Gene subset selection is essential for classification and analysis of microarray data. However, gene selection is known to be a very difficult task since gene expression data not only have high dimensionalities, but also contain redundant information and noises. To cope with these difficulties, this paper introduces a fuzzy logic based pre-processing approach composed of two main steps. First, ...