The spatial relationships plays an important role in GIS spatial data modeling, spatial query and spatial analysis etc. From the cognitive view, we represent and apply the information of relationships between spatial objects in the real world in computer system, study the fuzzy extension about description of spatial relationships at the base. Guided the spatial query the paper makes the model o...

In this paper, we introduce a fuzzy extension of the Rand index, a well-known measure for comparing two clustering structures. In contrast to an existing proposal, which is restricted to the comparison of a fuzzy partition with a non-fuzzy reference partition, our extension is able to compare two proper fuzzy partitions with each other. Elaborating on the formal properties of our fuzzy Rand ind...

Clustering is a widely applied tool of data mining to detect the hidden structure of complex multivariate datasets. Hence, clustering solves two kinds of problems simultaneously, it partitions the datasets into cluster of objects that are similar to each other and describes the clusters by cluster prototypes to provide some information about the distribution of the data. In most of the cases th...

Neutrosophic hesitant fuzzy set is the generalization of neutrosophic set and the hesitant fuzzy set, which can easily express the uncertain, incomplete and inconsistent information in cognitive activity, and the VIKOR (from Serbian:VIseKriterijumska Optimizacija I Kompromisno Resenje) method is an effective decision making tool which can select the optimal alternative by the maximum ‘‘group ut...

Fuzzy clustering techniques handle the fuzzy relationships among the data points and with the cluster centers (may be termed as cluster fuzziness). On the other hand, distance measures are important to compute the load of such fuzziness. These are the two important parameters governing the quality of the clusters and the run time. Visualization of multidimensional data clusters into lower dimen...

The primary issue involved in image and signal processing is to efficiently remove noise from a digital color image while preserving its features. A fuzzy filter is presented for the reduction of additive noise for digital color images. The filter consists of two sub filters. The first sub filter computes fuzzy distances among the color components of the central pixel and its neighborhood. Thes...

Keywords-Fuzzy reasoning, Fuzzy system, Variable weighted synthesis inference method, CRI method, Fuzzy control. 1. I N T R O D U C T I O N It is well known that fuzzy inference is a theoretical foundation of fuzzy control systems and fuzzy expert systems. At present, general fuzzy inference methods include the CRI (compositional rules of inference) method, (+,-)-centroid method, simple inferen...

The main contribution in this paper is to introduce an idea of fuzzy cdistance in fuzzy cone metric space. A common fixed point theorem for contraction mapping is established in fuzzy cone metric space by using fuzzy c-distance. Lastly the theorem is justified by a suitable example.

In the field of pattern recognition due to the fundamental involvement of human perception and inadequacy of standard Mathematics to deal with its complex and ambiguously defined system, different fuzzy techniques have been applied as an appropriate alternative. A pattern recognition system has to undergo basically the steps of preprocessing, feature extraction and selection, classifier design ...