Human-based quality control reduces the accuracy of this process. Also, the speed of decision making in some industries is very important. For removing these limitations in human-based quality control, in this paper, the design of an expert system for automatic and intelligent quality control is investigated. In fact, using an intelligent system, the accuracy in quality control is increased. It...

Expert systems are computer programs that emulate the reasoning process of a human expert or perform in an expert manner in a domain for which no human expert exists. They typically reason with uncertain and imprecise information. In this paper, we present a fuzzy expert system for a airplane navigation fault diagnosis system making the use of fuzzy set theory to deal with uncertainty. The faul...

Malaria, Typhoid, Tuberculosis, Sexually Transmitted Diseases, Urinary Tract Infection, Yellow fever, Hepatitis-B, Leprosy and Chicken Pox are the existing tropical diseases that are considered in this work. In sub-Saharan Africa, the application of fuzzy logic to the diagnosis of these diseases is still very sparse and in some places practically nonexistent. Fuzzy set theory and fuzzy logic ar...

This paper presents a particle swarm optimization (PSO)-based fuzzy expert system for the diagnosis of coronary artery disease (CAD). The designed system is based on the Cleveland and Hungarian Heart Disease datasets. Since the datasets consist of many input attributes, decision tree (DT) was used to unravel the attributes that contribute towards the diagnosis. The output of the DT was converte...

This paper deals with using fuzzy logic to minimize uncertainty effects in surveillance. It studies the conception of an efficient fuzzy expert system that had two characteristics: generic and robust to uncertainties. Analyzing distance between variables optimal and real values is the main idea of the research. Fuzzy inference system decides, then, about significant variables state: normal or a...

We propose in this paper to model of a rule based expert systems using the techniques of Fuzzy sets and Fuzzy logic. In the real world problem solving is the process of finding a solution when the path leading to that solution is uncertain. The Expert Systems need to have the ability to handle vague associations, for example by accepting the degree of correlations as numerical certainty factors...

Developing the expert system (ES) using conventional programming languages is very tedious task. Therefore, it is not surprising that tools have been developed that can support the knowledge engineer. Separate tools now exist to support the knowledge acquisition and to support the implementation. Fuzzy set theory is used to capture imprecision in inputs and outputs of models, and fuzzy expert s...

The endeavor of this work is to support the special education community in their quest to be with the mainstream. The initial segment of the paper gives an exhaustive study of the different mechanisms of diagnosing learning disability. After diagnosis of learning disability the further classification of learning disability that is dyslexia, dysgraphia or dyscalculia are fuzzy. Hence the paper p...

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...

In the last thirty years fuzzy logic became very popular. One can find solutions based on it in several fields from industrial systems to house appliances. Recently a new category of fuzzy systems gained more attention, the so called fuzzy rule interpolation (FRI) based systems. Owing to the low complexity of their rule bases, i.e. they can infer as well when only the relevant rules are known, ...