One benefit of fuzzy systems (Zadeh, 1965; Ruspini et al., 1998; Cox, 1994) is that the rule base can be created from expert knowledge, used to specify fuzzy sets to partition all variables and a sufficient number of fuzzy rules to describe the input/output relation of the problem at hand. However, a fuzzy system that is constructed by expert knowledge alone will usually not perform as required...

A system combining genetic algorithms and a fuzzy-rule induction routine has been developed. Two prototype expert systems, one derived analytically, and one derived e~~pir;lcal]y by tb.e fi~q++ inrlnrtinn ..L....v..V.. system, were developed to evaluate the utility of expert system technology relative to waste nondestructive assay (NDA) data review. Technical review of waste NDA measurement dat...

In the global market place, many companies have had to adapt their strategies to meet significant challenges. A strategy adopted by some companies has been international expansion via acquisitions. The need for expert knowledge to determine an appropriate company to acquire has been complicated by the sheer size of the global market place. The costs associated with this in relation to time and ...

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...

This paper is a statistical analysis of hybrid expert system approaches and their applications but more specifically connectionist and neuro-fuzzy system oriented articles are considered. The current survey of hybrid expert systems is based on the classification of articles from 1988 to 2010. Present analysis includes 91 articles from related academic journals, conference proceedings and litera...

Neural networks, which make no assumption about data distribution, have achieved improved image classification results compared to traditional methods. Unfortunately, a neural network is generally perceived as being a ‘black box’. It is extremely difficult to document how specific classification decisions are reached. Fuzzy systems, on the other hand, have the capability to represent classifica...

A fuzzy-modeling method for the emulation of expert decision behavior or for static as well as dynamic systems is presented. The input – output dataset of the system – or expert behavior is changed using fuzzy-sets into examples in linguistic form. These resulting examples build the fundament of the machine learning process for rule production (ID3). The fuzzy sets are optimized in order to min...

The importance of nutritional guidance grows as nutritional problems, such as obesity and type-2 diabetes, are becoming more common. Nutritional guidance is carried out by mapping the nutritional state of an individual using a food diary and by comparing the nutrition intake levels to the recommended reference values. Typically, the expert knowledge of a nutritionist is required to balance the ...

Fuzzy set theory and fuzzy logic are a highly suitable and applicable basis for developing knowledge-based systems in medicine for tasks such as the interpretation of sets of medical findings, syndrome differentiation in Eastern medicine, diagnosis of diseases in Western medicine, mixed diagnosis of integrated Western and Eastern medicine, the optimal selection of medical treatments integrating...