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...

CADIAG-1 is a medical expert system, based on a symbolic logic representation of medical relationships. Strong relationships such as confirming, excluding or obligatory occurrence are applied to confirm or exclude diagnoses. Weak relationships are represented by facultative and not confirming relationships (FN-relationships). Diagnostic hypotheses are established by systematic combination of sy...

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...

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...

Fuzzy logic and fuzzy set theory provide an important framework for representing and managing imprecision and uncertainty in medical expert systems, but the need remains to optimize such systems to enhance performance. This paper presents a general technique for optimizing fuzzy models in fuzzy expert systems (FES’s) by simulated annealing (SA) and N -dimensional hill climbing simplex method. T...

Before beginning the research that led to "Probabilistic logic" [11 ], I had participated with Richard Duda, Peter Hart, and Georgia Sutherland on the PROSPECTOR project [3]. There, we used Bayes' rule (with some assumptions about conditional independence) to deduce the probabilities of hypotheses about ore deposits given (sometimes uncertain) geologic evidence collected in the field [4]. At th...

This article presents the development of the knowledge base and inference motor for an Automated Management System for developing Expert Systems and Fuzzy Classifier (SAGSECD). SAGSECD is a tool that can be used for any user with basics knowledge in the expert systems or fuzzy classifiers area for designing and implementing this kind of systems to solve several problems or situations that requi...

Efficient use of enterprise resource planning systems is the only way to achieve competitive advantage in many industries. However, many reports indicate high failure rate of ERP implementation projects and the lack of access to benefits and advantages that enterprises have expected from ERP deployment. Managers are concerned about being ready to deploy such a system. Despite its enormous cost,...