Traditional forecasting methods need strict assumptions such as normality and linearity. It is very difficult to satisfy these assumptions for real-world time series. Many realworld time series can be easily analyzed by using fuzzy time series methods since fuzzy time series methods do not require any strict assumptions. Therefore, fuzzy time series approaches have been getting more and more at...

In this paper, a nonconventional structure for a “fuzzy” controller is proposed. It does not require signal division, and it produces control surfaces similar to classical fuzzy controllers. The structure combines fuzzification, MIN operators, normalization, and weighted sum blocks. The fuzzy architecture is implemented as a VLSI chip using 2m n-well technology. A new fuzzification circuit, whi...

6 ABSTRACT Fuzzy logic plays an important role in the field of medicine. Many diseases are diagnosed using fuzzy logic. Heart disease is the number one killer to the human community throughout the world. This study was conducted to diagnosis the heart disease among the patients. The components of this study are Fuzzification, Generating rules for Advanced Fuzzy Resolution Mechanism and defuzzif...

ABSTRACT: In this paper a non-conventional structure for a “fuzzy” controller is proposed. It does not require signal division, and it produces control surfaces similar to classical fuzzy controllers. The structure combines fuzzification, MIN operators, normalization and weighted sum blocks. The fuzzy architecture is implemented as a VLSI chip using 2um n-well technology. A new fuzzification ci...

Nowadays in this competitive world of job seekers, the necessity of job makes many recruiters to provide more cautious on their selection process. The recruitment process is definitely a fuzzified anomaly for all the components available in the environment. The art of deception also changes its face with a modern artistic fashion. This paper deals with the uncertainty features which play the ma...

Support vector machine (SVM) is sensitive to the outliers, which reduces its generalization ability. This paper presents a novel support vector regression (SVR) together with fuzzification theory, inconsistency matrix and neighbors match operator to address this critical issue. Fuzzification method is exploited to assign similarities on the input space and on the output response to each pair of...

Uncertainty is an inherent property of all living systems. Curiously enough, computational models inspired by biological systems do not take, in general, under consideration this essential aspect of living systems. In this paper, after introducing the notion of a multi-fuzzy set (i.e. an orthogonal approach to the fuzzification of multisets), we introduce two variants of P systems with fuzzy co...

This paper expresses the prominent features of the fuzzy expert system by applying the algorithm Fuzzy Assessment Methodology using K ratio. To diagnosis the diabetes Fuzzy Assessment Methodology using k ratio is developed. Fuzzy Expert System consists of following elements such as Fuzzification interface, Fuzzy Assessment Methodology using K ratio and Defuzzification interface. The crisp value...