The notion of uncertainty in expert systems is dealing with vague data, incomplete information, and imprecise knowledge. Different uncertainty types which are imprecision, vagueness, ambiguity, and inconsistence need different handling models. Uncertain knowledge representation and analysis is an essential issue. Classical probability, Bayes theory, Dempster–Shafer theory, certainty factor and ...

One of the advantages systems based on fuzzy logic (fuzzy systems) is possibility a soft switch from one set values input parameters system to another, when different conclusions are drawn for sets these values. A type 2 direct generalization an ordinary set. In this paper, we review some branches theory type-2 and systems. We discuss operations sets, relations, centroids describe functional re...

Intelligent traffic signal control (TSC) system is important for the alleviation of traffic congestion. Usually, most of the researches about TSC focused on single intersection based on type-1 fuzzy set. Compared with type-1 fuzzy logic controller (FLC), type-2 FLC can deal with more uncertainties in the road traffic control system. Therefore, a type-2 FLC optimized by NSGAII (T2-NSGAII) is des...

in this paper, we present a revised similarity measure based onchen-and-chen's similarity measure for fuzzy risk analysis. the revisedsimilarity measure uses the corrected formulae to calculate the centre ofgravity points, therefore it is more  effective than the chen-and-chen'smethod. the revised similarity measure can overcome the drawbacks of theexisting methods. we have also proposed a new ...

This paper presents the fuzzy expert system for intelligent support of decision making about cause of stone construction crack of building. The system is based on some linguistic expert expressions formalised by 9 fuzzy knowledge bases. Tuning of fuzzy rules by genetic algorithms provided a good concordance between real causes of cracks and results of decision making by the system.

A majority of efforts in terms of technology commercialization have failed; however, the issue of commercialization and its high importance are agreed upon by policymakers, entrepreneurs, and researchers. This shows the high complexity of the commercialization process. One of the main solutions to overcome the commercialization problems is to predict the success of technology commercialization ...

The stock market has always been an attractive area for researchers since no method has been found yet to predict the stock price behavior precisely. Due to its high rate of uncertainty and volatility, it carries a higher risk than any other investment area, thus the stock price behavior is difficult to simulation. This paper presents a “data mining-based evolutionary fuzzy expert system” (DEFE...

Medical expert systems being used for disease diagnosis where the patient’s symptoms and other details are inputs and the system diagnose the disease, recommend treatment or drugs which may be prescribed. Medical diagnosis involves several levels of uncertainty and imprecision. This paper reviews the various expert systems used not only for diabetes diagnosis but also gives the treatment and me...

This paper presents a fuzzy-based system that is used for maintenance planning of road pavements. The system has been developed based on knowledge elicitation from experienced maintenance engineers using fuzzy logic. The system includes functions for pavement condition and deterioration prediction, feasible treatment assessment in each pavement section, and maintenance planning in a road networ...

One of the most important stages in the urban transportation planning procedure is predicting the rate of trips generated by each trac zone. Currently, multiple linear regression models are frequently used as a prediction tool. This method predicts the number of trips produced from, or attracted to each trac zone according to the values of independent variables for that zone. One of the main li...