In this paper, conventional validity indexes are reviewed and the shortcomings of the fuzzy cluster validation index based on intercluster proximity are examined. Based on these considerations, a new cluster validity index is proposed for fuzzy partitions obtained from the fuzzy c-means algorithm. The proposed validity index is defined as the average value of the relative intersections of all p...

In this paper we give a possible model for handling uncertain information. The concept of fuzzy knowledge-base will be defined as a quadruple of any background knowledge, defined by the proximity of predicates and terms; a deduction mechanism: a fuzzy Datalog program; a connecting algorithm, which connects the background knowledge with the program and a decoding set of the program, which help u...

In this work we present a model for handling uncertain information. The concept of fuzzy knowledge-base is defined as a quadruple of background knowledge. Specifically, the latter is defined by the proximity of predicates and terms; a deduction mechanism: a fuzzy Datalog program; a connecting algorithm, which connects the background knowledge with the program, and a decoding set of the program ...

Fuzzy Similarity measures are used to compare different kinds of objects such as images. Their definitions are based on proximity measures, operations on fuzzy sets etc. which makes different propositions of properties of similarity measures. Consequently, the latter are not common for all similarity measures presented in literature. In this paper we present and discuss the properties of fuzzy ...

In this paper we introduce an application of intervalvalued systems to the segmentation of prostate ultrasound images. The system classifies each pixel as prostate or background. The input variables are the values of each pixel in different processed images as proximity, edginess and enhanced image. The system has 20 rules and is trained with ideal images segmented by an expert. Interval-valued...

Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on the cardinality of the fuzzy subsets and their complementaries that represent the objects under study, without applying any crisp property when the various elements that compose the process are fuzzified. From this perspective we define a family of fuzzy similarity indexes which includes a s...

Routing information plays a vital role in Mobile Ad-hoc Network (MANET). In MANET, each node maintains routing information that assists the routing process. Routing nodes and their routing attributes are essential in determining the performance of MANET. Thus, it is necessary to obtain knowledge on routing nodes and their attributes. Keeping this in view, we have proposed a model that uses a fu...

A new clustering algorithm for proximity data, called RECM (Relational evidential c-means) is presented. This algorithm generates a credal partition, a new clustering structure based on the theory of belief functions, which extends the existing concepts of hard, fuzzy and possibilistic partitions. Two algorithms, EVCLUS (Evidential Clustering) and ECM (Evidential c-Means) were previously availa...

Sociological research shows that friendship and partner choice tend to reveal a bias toward social similarity. These relations are ruled by the so called “proximity principle” which states that the more similar two individuals are, the more likely they will become friends. However, proximity, similarity or friendship are concepts with blurred edges and grades of membership (acquaintances, frien...

Multi-Document summarization strictly needs distinguishing the similarity between sentences & paragraphs of texts because repeated sentences shouldn’t exist in final summary so in order to applying this anti-redundancy we need a mechanism that can determining semantic similarities between sentences and expressions and paragraphs and finally between texts. In this paper it’s used a fuzzy approac...