Fuzzy C-means (FCM) is an important clustering algorithm with broad applications such as retail market data analysis, network monitoring, web usage mining, and stock prediction. Especially, parameters in FCM have influence on results. However, a lot of did not solve the problem, that is, how to set parameters. In this study, we present kind method for computing values according role process. Ne...

To recognize functional sites within a protein sequence, the non-numerical attributes of the sequence need encoding prior to using a pattern recognition algorithm. The success of recognition depends on the efficient coding of the biological information contained in the sequence. In this regard, a bio-basis function maps a non-numerical sequence space to a numerical feature space, based on an am...

In this paper, a possibilistic Hopfield neural network (PHNN) has been proposed for clustering and subsequently applied to brain hemorrhage image segmentation based on a series of CT images. The neural network structure has been implemented by imbedding the weighting possibilistic c-means algorithm into a Hopfield neural network. The network solved the coincidental cluster problem by using a we...

The current models and methods for PLP are usually restricted on some special types and usually the same type of possibilistic distribution. This paper focuses on linear programming problems with general possibilistic resources (GRPLP) and linear programming problems with general possibilistic objective coe cients (GOPLP). By introducing some new concepts of the largest most possible point, the...

-There are various clustering models introduced for unsupervised learning. PFCM or the possibilistic c-means model was proposed in 2005. PFCM produces mainly three values: the typicality values, membership values and the centres of the clusters. It is a hybrid model of PCM and FCM. We propose an extension to PFCM so that it can be used to cluster the text files. Keywords— possibilistic model, f...

1106 | P a g e Abstract--Image processing plays an important role in medical field because of its capability. Particularly, image segmentation offer several guides in medical field for analyzing the captured image. Usually, the medical images are captured via different medical image acquisition techniques. The captured image may be affected by noise because of some faults in the capturing devis...

In possibility theory, there are two kinds of possibilistic causal networks depending if possibilistic conditioning is based on the minimum or on the product operator. Similarly there are also two kinds of possibilistic logic: standard (min-based) possibilistic logic and quantitative (product-based) possibilistic logic. Recently, several equivalent transformations between standard possibilistic...

Fuzzy clustering is a useful tool for capturing intrinsic structure of data sets. This paper proposes several formulations for soft transition of fuzzy memberships from probabilistic partition to possibilistic one. In the proposed techniques, the free memberships are given by introducing additional penalty term used in Possibilistic c-Means. The new features of the proposed techniques are demon...