Fuzzy Analysis of Statistical Evidence (FASE) is utilizing the fuzzy set and the statistical theory for solving problems of pattern recognition and/or classification. Several features of FASE are similar to the human judgment. It can evaluate the weight of statistical evidence (information); it can update inference with new information; and it can incorporate missing data. Furthermore, since it...

The objective of this study is to design a fuzzy expert system for performance assessment of health, safety, environment (HSE) and ergonomics system factors in a gas refinery. This will lead to a robust control system for continuous assessment and improvement of HSE and ergonomics performance. The importance of this study stems from the current lack of formal integrated methodologies for interp...

Fuzzy Association Rule Mining Expert-Driven (FARME-D) approach to knowledge acquisition is proposed in this paper as a viable solution to the challenges of rule-based unwieldiness and sharp boundary problem in building a fuzzy rule-based expert system. The fuzzy models were based on domain experts’ opinion about the data description. The proposed approach is committed to modelling of a compact ...

There exist in the literature today many contributions dealing with the incorporation of fuzzy logic in expert systems. However, unfortunately, much of what has been proposed can only be applied to small-scale expert systems; that is, when the number of rules is in the dozens as opposed to in the hundreds. The more traditional (nonfuzzy) expert systems are able to cope with large numbers of rul...

Recently, there is great deal of interest in the use of fuzzy expert systems in control applications. Controllers based on fuzzy logic belong to the class of static or memoryless nonlinear controllers and provide better control than is possible using linear control. The major strength of fuzzy controllers lies in the way a nonlinear output mapping of a number of inputs can be specified easily u...

Aggregation of information represented by membership functions is a central matter in intelligent systems where fuzzy rule base and reasoning mechanism are applied. Typical examples of such systems consist of, but not limited to, fuzzy control, decision support and expert systems. Since the advent of fuzzy sets a great number of fuzzy connectives, aggregation operators have been introduced. Som...

A framework of integrated expert systems based on fuzzy Petri net, called fuzzy Petri net based expert system (FPNES) are proposed for bridge damage assessment. Major features of FPNES include: reasoning for uncertain and imprecise information; knowledge representation through the use of hierarchical fuzzy Petri nets; reasoning mechanism based on fuzzy Petri nets; and explanation of reasoning p...

Design and implementation of multi-agent system with usage of expert systems and fuzzy logic for robotic soccer control is shown. This approach is capable of effective recognition of the game situation and deducing of demanded speed vector for every possible case. Low conceptual distance ensures easy transfer of expert knowledge to the inference system.

This paper summarizes some results of the authors’ research that have been carried out in recent years on generalization of conventional aggregation operators. Aggregation of information represented by membership functions is a central matter in intelligent systems where fuzzy rule base and reasoning mechanism are applied. Typical examples of such systems consist of, but not limited to, fuzzy c...

The allergy based diagnostic expert system (ABExS) is designed to help or assist the psychology doctors to diagnosing the various mental disorders related to human. ABExS can be used to perform some evaluation of patient’s physical and emotional symptoms to diagnose the particular disorder In this expert allergy system there are of different types of methods to find out about the various types ...