Fuzzy{logic theory is a valuable tool to structure ad{hoc designs where model{based designs are not suitable or even not available. There exist numerous examples of industry proven fuzzy{logic solutions in the domain of control, pattern recognition and expert systems. The design of fuzzy systems demand a great deal of experience and intuition. Due to the many degrees of freedom in the design of...

In his pioneering papers, Igor Zaslavsky started an algorithmic (constructivist) analysis of fuzzy logic. In this paper, we extend this analysis to fuzzy mathematics and fuzzy data processing. Specifically, we show that the two mathematically equivalent representations of a fuzzy number – by a membership function and by α-cuts – are not algorithmically equivalent, and only the α-cut representat...

Due to the multiplicity of standards and complex rules; maintenance, repair and servicing of machinery could be done only by the fully qualified and proficient experts. Since the knowledge of such experts is not available all times, using expert systems can help to improve the maintenance process. To address this need and the uncertainty of the maintenance process indicators, this research prop...

This paper presents a genetic algorithm (GA) that automatically constructs the knowledge base used by fuzzy decision support systems (FDSS). The GA produces an optimal approximation of a set of sampled data from a very small amount of input information. The main interest of this method is that it can be used to automatically generate (without the help of an expert) a fuzzy knowledge base ± i.e....

Fuzzy models have been designed to represent approximate or imprecise relationships in complex systems and have been successfully employed in control systems, expert systems, and decision analysis. Classically, fuzzy models were built from human expertise and knowledge of the system being modeled. As systems have grown more complex it has become increasingly difficult to construct models direct...

For building design, computational intelligence systems use a knowledge base formed by means of neural network and fuzzy logic (neuro-fuzzy) techniques, from a building design database. The application of such a system to a building design task was preliminarily demonstrated earlier. The present research describes a systematic neural fuzzy modelling of data that forms a knowledge base in a hier...

Knowledge acquisition is a key phase in construction of expert systems. This process is very much dependent on the nature of the domain knowledge. In particular, knowledge acquisition is a tedious task when modeling domains with tacit knowledge. Despite fuzzy logic has been used for knowledge acquisition in such domains, a large portion of the process is manually operated. This paper presents a...

The biggest challenge for agents’ collaboration in Decision Support Systems is resolving possible conflicts of knowledge. When coordinating activities, either in a cooperative or a competitive environment, conflicts may arise and three basic strategies to solve these conflicts are by means of negotiation, mediation and arbitration. Following these strategies; different intelligent techniques de...