In this paper, we discussed binary fuzzy codes over a vector space F2n by relating classical with the probability of symmetric channel (BSC) for receiving sent codeword correctly. We used weight error patte...

This chapter deals with the construction of distance and similarity measures by utilizing the theoretical advantages of the fuzzy implications. To this end the basic definitions of fuzzy implications are initially discussed and the conditions of typical distance and similarity measures that need to be satisfied are defined next. On the basis of this theory a straightforward methodology for buil...

This paper considers a flow shop problem with imprecise processing times with the objective to minimize the makespan. The processing times are described by triangular fuzzy numbers. The issue that arises is how to rank the constructed job sequences with respect to their obtained makespans, which are fuzzy numbers. A new distance measure between fuzzy makespans is introduced which includes an op...

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...

logistics outsourcing has been at the top of the management agenda during recent decades. the selection of the proper service supplier is the key to success in logistic outsourcing firms could select the right supplier by applying appropriate methods and selection criteria. in this paper a new framework is proposed on the basis of weighted additive fuzzy programming approach and linear programm...

Using fuzzy filters in the sense of P. Eklund and W. Gähler [2], it turns out that fuzzy preuniform convergence spaces introduced in [11] form a strong topological universe in which fuzzy topological spaces as well as fuzzy (quasi) uniform spaces can be studied. Thus, better tools such as the existence of natural function spaces, the existence of one-point extensions (and consequently, the here...

The distance measure is an important criterion in any clustering algorithm. This paper shows how fuzzy clustering results can be improved by introducing a weighting factor in the inter-objects distance measures. New weighted versions of four well-known distance measures are considered. These distances are tested, using the fuzzy c-means algorithm, on three datasets. Experimental results show th...

FCM (fuzzy c-means algorithm) based on Euclidean distance function converges to a local minimum of the objective function, which can only be used to detect spherical structural clusters. The added fuzzy covariance matrices in their distance measure were not directly derived from the objective function. In this paper, an improved Normalized Clustering Algorithm Based on Mahalanobis distance by t...

In this paper, a new approach is presented to fit arobust fuzzy regression model based on some fuzzy quantities. Inthis approach, we first introduce a new distance between two fuzzynumbers using the kernel function, and then, based on the leastsquares method, the parameters of fuzzy regression model isestimated. The proposed approach has a suitable performance to<b...