This paper examines the traditional architecture of fuzzy expert reasoning and suggests a reorientation, which is simpler, more intuitive, and more implementable. This new approach centers on first determining the degree of satisfaction that a rule applies to the current situation, and then using this degree of satisfaction to qualify the rule’s conclusion. This provides a theoretical basis for...

Policy-makers and planners have to make decisions in the face of varying degrees of uncertainty and risk. SimCoastTM is an intelligent computing system designed to addresses these problems explicitly. Here we look at how fuzzy logic and expert systems two of the fundamental approaches within SimCoastTM can be used to improve decision-making in relation to conditions of high levels of uncertaint...

In this paper, an integrative strategy is proposed to solve synthesis problems in non-connict cases in distributed expert systems (DESs) based on fuzzy logic operations. In this strategy, the synthesis situations is identiied as overlap and disjoint cases based on relationships of the evidence which is used to derive the solution from expert systems (ESs). Two synthesis models, Strategy1, and S...

After a basic introduction of fuzzy logic, we discuss its role in artiicial and computational intelligence. Then we present innovative applications of fuzzy logic, focusing on fuzzy expert systems, with one typical example explored in some detail. The article concludes with suggestions how artiicial intelligence and fuzzy logic can beneet from each other.

This paper presents an expert system aimed at evaluating firms and business units. It makes us of fuzzy logic and integrates financial, strategic, managerial aspects, processing both quantitative and qualitative information. Twenty-nine value drivers are explicitly taken into account and combined together via “if-then” rules to produce an output. The output is a real number in the interval [0,1...

The Hand Sign Classification (HSC) system classifies hand movement data into Australian Sign Language (AUSLAN) signs. It is built as a fuzzy expert system with an adaptive engine that trains the system to handle variations in the movement data, or to adapt to differences amongst signers. Adaptive fuzzy systems are often compared with neural networks in their adaptability, but unlike neural netw...