Overlapping community detection is a popular topic in complex networks. As compared to disjoint community structure, overlapping community structure is more suitable to describe networks at a macroscopic level. Overlaps shared by communities play an important role in combining different communities. In this paper, two methods are proposed to detect overlapping community structure. One is called...

Machine learning, data mining, and several related research areas are concerned with methods for the automated induction of models and the extraction of interesting patterns from empirical data. Automated knowledge acquisition of that kind has been an essential aspect of artificial intelligence since a long time and has more recently also attracted considerable attention in the fuzzy sets commu...

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 endeavor of this work is to support the special education community in their quest to be with the mainstream. The initial segment of the paper gives an exhaustive study of the different mechanisms of diagnosing learning disability. After diagnosis of learning disability the further classification of learning disability that is dyslexia, dysgraphia or dyscalculia are fuzzy. Hence the paper p...

We utilize a competitive co-evolutionary algorithm (CA) in order to optimize the parameter set of a Fuzzy-System for job negotiation between CommunityGrids. In a Community-Grid, users are submitting jobs to their local High Performance Computing (HPC) sites over time. Now, we assume that Community-Grids are interconnected such that the exchange of jobs becomes possible: Each Community strives f...

In this paper some research trends are presented concerning the application of fuzzy techniques to model flexible systems for the access to information on the WWW. The focus is on the definition of flexible systems, i.e. systems that can represent and manage the vagueness and uncertainty which is characteristic of the process of information searching and retrieval. We also identify some researc...

Over the past years, methods for the automated induction of models and the extraction of interesting patterns from empirical data have attracted considerable attention in the fuzzy set community. This paper briefly reviews some typical applications and highlights potential contributions that fuzzy set theory can make to machine learning, data mining, and related fields. The paper concludes with...

The year 2005 is marked by the 40th anniversary of fuzzy set theory, as it was in 1965 that Lotfi Zadeh published his famous seminal paper that fostered the rise of a whole new community, researching theory and applications of fuzzy sets and systems. Throughout the years, fuzzy logic was frequently met with skepticism, not in the least because of its often misunderstood name. Nevertheless, our ...

Due to the increasing frequency of natural and man-made disasters, scientific community has paid considerable attention concept resilience engineering. On other hand, authorities decision-makers have been focusing their efforts on developing strategies that can help increase different types extreme events. Since it is often impossible prevent every risk, focus adapting managing risks in ways mi...

Many geographical applications need to model spatial phenomena with vague or indeterminate boundaries and interiors. A popular paradigm adopted by the GIS community for this task at the modeling level is fuzzy set theory. A spatial object is fuzzy if locations exist that cannot be assigned completely to the object or to its complement. In previous work, we have proposed an abstract data model o...