Fuzzy project scheduling has interested several researchers in the past two decades; about 20 articles have been written on this issue. Contrary to stochastic project-scheduling approaches that are used by many project schedulers, and even if the axiomatic associated to the theory of probabilities is not always compatible with decision-making situations, fuzzy project-scheduling approaches that...

In this paper, a system consisting of single multi-state element (MSE) with performance rates and transition intensities presented as fuzzy values is introduced. Due to the lack, inaccuracy or fluctuation of collected data, it is often too difficult to evaluate the performance rates and transition intensities of multi-state element/system with precise value, especially in the continuous degrada...

Information fusion introduces special operators ◦ in probability theory and fuzzy theory. Some serious data certify in each cases these two quite distinct techniques. This communication will show that four postulates are the unique aim of these two theories. Evidence theory and fuzzy set theory replace often probabilities in medicine, economy and control. Fuzzy theory is used for example in Jap...

Fingerprint identification is one of the salient areas in biometric identification system. The quality of the fingerprint image is imperative for a veracious matching process. Normally, the contrast of the image is improved during the preprocessing phase of fingerprint matching. Contrast refers to the difference between two contiguous pixels. There are several enhancement techniques available f...

Multiple classifiers combination is a technique that combines the decisions of different classifiers as to reduce the variance of estimation errors and improve the overall classification accuracy. A new multiple classifiers fusion method integrated classifier selection and classifier combination is proposed in this paper. It is base on interval-valued fuzzy permutation. Firstly, normalize all c...

Conventionally, we use a chi-square test of homogeneity to determine whether the cell probabilities of a multinomial are equal. However, this process of testing hypotheses is based on the assumption of two-valued logic. If we collect questionnaire data using fuzzy logic, i.e., we record the category data with memberships instead of with a 0-1 type, then the conventional test of goodness-of-fit ...

Contrast Stretching is an important part in medical image processing applications. Contrast is the difference between two adjacent pixels. Fuzzy statistical values are analyzed and better results are produced in the spatial domain of the input image. The histogram mapping produces the resultant image with less impulsive noise and smooth nature. The probabilities of gray values are generated and...

Image thresholding is very useful for keeping the significant part of an image and getting rid of the unimportant part or noise. This holds true under the assumption that a reasonable threshold value is chosen. The study of image thresholding techniques in earthquake engineering, remote sensing, geology and geophysics seems to be extremely important for recognition of certain patterns such as f...

One of the most frequently used models for classification tasks is the Probabilistic Neural Network. Several improvements of the Probabilistic Neural Network have been proposed such as the Evolutionary Probabilistic Neural Network that employs the Particle Swarm Optimization stochastic algorithm for the proper selection of its spread (smoothing) parameters and the prior probabilities. To furthe...

This paper presents a nuclear case study, in which a fuzzy inference system (FIS) is used as alternative approach in risk analysis. The main objective of this study is to obtain an understanding of the aging process of an important nuclear power system and how it affects the overall plant safety. This approach uses the concept of a pure fuzzy logic system where the fuzzy rule base consists of a...