This paper will present a novel concept of expected values of fuzzy variables, which is essentially a type of Choquet integral and coincides with that of random variables. In order to calculate the expected value of general fuzzy variable, a fuzzy simulation technique is also designed. Finally, we construct a spectrum of fuzzy expected value models, and integrate fuzzy simulation, neural networ...

this paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. this estimation method is obtained by implementing ridge regression learning algorithm in the la- grangian dual space. the distance measure for fuzzy numbers that suggested by diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...

In this paper we explore the applicability of Fuzzy C-Means clustering technique to student allocation problem that allocates new students to homogenous groups of specified maximum capacity, and analyze effects of such allocations on the academic performance of students. This paper also presents a Fuzzy set and Regression analysis based rules based Fuzzy Expert System model which is capable of ...

A Novel hybrid segmentation method has been developed for detection of masses in digitized mammograms using three parallel approaches: adaptive thresholding method, Gabor filtering and fuzzy entropy feature as a computer-aided detection(CAD) scheme. The algorithm consists of the following steps: a) Preprocessing of the digitized mammograms including identification of region of interest (ROI) as...

| Fuzzy logic and fuzzy set theory provide an important framework for representing and managing impre-cision and uncertainty in medical expert systems, but the need remains to optimise such systems to enhance performance. This paper presents a general technique for optimizing fuzzy models in fuzzy expert systems by simulated annealing and N-dimensional hill climbing simplex method. The applicat...

This paper addresses the fault detection of a cracked cantilever beam using a hybrid artificial intelligence technique. The hybrid technique used here uses a fuzzy-neuro controller. The fuzzy-neuro controller has two parts. The first part is comprised of the fuzzy controller, and the second part is comprised of the neural controller. The input parameters of the fuzzy controller are relative dev...

Takagi–Sugeno (TS) fuzzy modeling technique, a black-box discrete-time approach for system identification, has widely been used to model behaviors of complex dynamic systems. Analytical structure of TS fuzzy models, however, is presently unknown, nor is its possible connection with the traditional models, causing at least two major problems. First, the fuzzy models can hardly be utilized to des...