Neuro-fuzzy [Jang,1997][Abraham,2005] are hybrid systems that combine the learning capacity of neural nets [Haykin,1999] with the linguistic interpretation of fuzzy inference systems [Ross,2004]. These systems have been evaluated quite intensively in machine learning tasks. This is mainly due to a number of factors: the applicability of learning algorithms developed for neural nets; the possibi...

Lee, Stolfo, and Mok have previously reported the use of association rules and frequency episodes for mining audit data to gain knowledge for intrusion detection. The integration of association rules and frequency episodes with fuzzy logic can produce more abstract and flexible patterns for intrusion detection, since many quantitative features are involved in intrusion detection and security it...

The integration of association rules and correlation rules with fuzzy logic can produce more abstract and flexible patterns for many real life problems, since many quantitative features in real world, especially surveying the frequency of plant association in any region is fuzzy in nature. This paper presents a modification of a previously reported algorithm for mining fuzzy association and cor...

In a binary choice voting scenario, voters may have fuzzy preferences but are required to make crisp choices. In order to compare a crisp voting procedure with more general mechanisms of fuzzy preference aggregation, we first focus on the latter. We present a formulation of strategy-proofness in this setting and study its consequences. On one hand, we achieve an axiomatic recommendation of the ...

An increasing number of applications require the integration of data from various disciplines, which leads to problems with the fusion of multi-source information. In this paper, a special information structure formalized in terms of three indices (the central presentation, population or scale, and density function) is proposed. Single and mixed Gaussian models are used for single source inform...

Although signi cant progress has been made in developing multidatabase systems that integrate component databases containing crisp data, little has been reported on integrating fuzzy databases in such systems. In this paper, we investigate the problem of integrating fuzzy relational databases in a multidatabase system. We identify new types of con icts that may occur in schemas and data due to ...

In this paper a fuzzy interaction among robots in a group is presented as an alternative solution to the classical protocols used in architectures for the cooperation of robots. In order to achieve this goal, the integration of previous works carried out on fuzzy behaviors and on cooperative architectures at the Intelligent Agents Lab. (LAI) has been used. This cooperation/coordination protocol...

Multi-source information fusion usually deals with redundant sources; the goal is to aggregate decisions, or evidence which supports one or another class. Many frameworks are then available: OWA, fuzzy integrals, etc. In this paper we are interested in managing complementary information sources. The integration is done using a fuzzy rule base. The rules are generated using a fuzzy decision tree...

This paper presents a fuzzy neural network approach to virtual product design. Contemporary design process requires the development of a new computational intelligent methodology that involves intelligent integration of design, analysis and evaluation, simulation and optimization in a virtual environment. In the paper, a soft-computing framework is developed for engineering design based on a hy...

Spatial relations play important role in computer vision, scene analysis, geographic information systems (GIS) and content based image retrieval. Analyzing spatial relations by Force histogram was introduced by Miyajima et al [10] and largely developed by Matsakis [12] who used a quantitative representation of relative position between 2D objects. Fuzzy Allen relations are used to define the fu...