In this study fuzzy arithmetic is presented as a tool to tackle the prediction of the amount of barium, strontium and calcium sulfates scales in oilfield operations. Since the shape of fuzzy numbers’ membership functions is a spread representative of the whole possible values for a special model parameter, fuzzy numbers are able to consider the uncertainties in parameter determinations and thus...

In this paper a new variation of Hough Transform is proposed. It can be used to detect shapes or contours in an image, with better accuracy, especially in noisy images. The parameter space of Hough Transform is split into fuzzy cells which are de ned as fuzzy numbers. This fuzzy split provides the advantage to use the uncertainty of the contour point location which is increased when noisy image...

The expectation function of fuzzy variable is an important and widely used criterion in fuzzy optimization, and sound properties on the expectation function may help in model analysis and solution algorithm design for the fuzzy optimization problems. The present paper deals with some analytical properties of credibilistic expectation functions of fuzzy variables that lie in three aspects. First...

This article describes an approach to automatically build a Takagi-Sugeno fuzzy model (TSK-model) based on a set of input-output data (system identification). Identifying rule-based fuzzy models consists of two parts: structure modeling, i. e. determining the number of rules and input variables involved respectively, and parameter optimization, i. e. optimizing the rules consequences and the lo...

⎯The passivity and feedback passification problems of fuzzy systems with parameter uncertainties and impulse are first presented in this paper. Based on the parallel distributed compensation (PDC) technique, some passivity and passification conditions are proposed in terms of linear matrix inequalities (LMIs). Numerical examples are given to show the correctness and effectiveness of our theoret...

This paper presents a theoretical proposal of fuzzy instrumental variable (FIV) methods for nonlinear discrete time systems identification and parameter estimation in noisy environment based on the fuzzy instrumental variable concept. The theoretical analysis is presented using a suitable formulation associated to Takagi-Sugeno (TS) fuzzy model. The complexity of the algorithm is quite low and ...

The purpose of this study is to define the concepts of Tsallis entropy and conditional Tsallis entropy of fuzzy partitions and to obtain some results concerning this kind entropy. We show that the Tsallis entropy of fuzzy partitions has the subadditivity and concavity properties. We study this information measure under the refinement and zero mode subset relations. We check the chain rules for ...

Fuzzy Decision Tree induction is a powerful methodology to extract human interpretable classification rules. The induction of fuzzy decision tree is done using popular Fuzzy ID3 algorithm [1, 2]. The other parameters which influence the performance of fuzzy decision tree are cut standard parameter  and leaf selection threshold parameter th  . Generally these parameters are to be selected heur...

This paper presents a process to obtain the solution (or flux) of a fuzzy delay system and to determine the fuzzy expected curve for the HIV (human immunodeficiency virus) when HIV-positive individuals receive antiretroviral therapy. This delay is defined as the time between the infection of a CD4+ type T-lymphocyte cell by the virus and the production of new virus particles. The intracellular ...

Soft Clustering plays a very important rule on clustering real world data where a data item contributes to more than one cluster. Fuzzy logic based algorithms are always suitable for performing soft clustering tasks. Fuzzy C Means (FCM) algorithm is a very popular fuzzy logic based algorithm. In case of fuzzy logic based algorithm, the parameter like exponent for the partition matrix that we ha...