In a great deal of literature on fuzzy regression analysis, most of research has focused on some predefined parametric forms of fuzzy regression relationships, especially on the fuzzy linear regression models. In many practical situations, it may be unrealistic to predetermine a fuzzy parametric regression relationship. In this paper, a fuzzy nonparametric model with crisp input and LR fuzzy ou...

Abstract: This paper proposes new matrix methods for solving positive solutions for a positive Fully Fuzzy Linear System (FFLS). All coefficients on the right hand side are collected in one block matrix, while the entries on the left hand side are collected in one vector. Therefore, the solution can be gained with a non-fuzzy common step. The necessary theorems are derived to obtain a necessary...

This paper shows how knowledge, in the form of fuzzy rules, can be derizted from a superuised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning, which simplifies the network structure by remooing excessiae recognition categories and weights; and quantization of continuous learned weights, which allows the final system state to be translated into a usab...

Super Resolution (SR) reconstruction is a procedure of attaining the High resolution (HR) images from a set of noisy and blurred low resolution (LR) observations. In this paper a novel SR algorithm is proposed by developing a fuzzy based Bicubic interpolation algorithm to improve the resolution of the image. The algorithm significantly improves the resolution, quality and enhances the color inf...

In recent work authors have proposed four new aggregation operators based on the arithmetic and geometric means of the Land Ror right side and left side apex angles for triangular [1] [2] and trapezoidal [3] [4] fuzzy numbers respectively. In this paper authors propose a new aggregation operator for TFNs in which the Land Rmembership function lines of the aggregate TFN have slopes which are the...

in this paper, we deal with fuzzy random variables for inputs andoutputs in data envelopment analysis (dea). these variables are considered as fuzzyrandom flat lr numbers with known distribution. the problem is to find a method forconverting the imprecise chance-constrained dea model into a crisp one. this can bedone by first, defuzzification of imprecise probability by constructing a suitablem...

Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for esti...