This paper is an applied approach to grey relation analysis to select representative criteria among a large set of available choices. The method of grey related analysis to solve Fuzzy Multiple Attribute Decision Making (FMADM) problem, using interval fuzzy numbers is considered. The method standardizes inputs through norms of interval number vectors. Interval valued indices are used to apply multiplicative operations over interval numbers instead of that In this paper, the method of grey related analysis use the idea of minimizing a distance function. However, grey related analysis reflects a form of fuzzification of inputs, and uses different calculations, to include different calculation of norms. The method is demonstrated on a practical problem that selection of materials related to the wind turbine blades for decision maker estimates of alternative performance on different scales.

Denoising of natural images is the fundamental and challenging research problem of Image processing. This problem appears to be very simple however that is not so when considered under practical situations, where the type of noise, amount of noise and the type of images all are variable parameters, and the single algorithm or approach can never be sufficient to achieve satisfactory results. Fourier transform method is localized in frequency domain where the Wavelet transform method is localized in both frequency and spatial domain but both the above methods are not data adaptive .Independent Component Analysis (ICA) is a higher order statistical tool for the analysis of multidimensional data with inherent data adaptiveness property. The noise is considered as Gaussian random variable and the image data is considered as non-Gaussian random variable. Specifically the Natural images are considered for research as they provide the basic knowledge for understanding and modeling of human vision system and development of computer vision systems. This paper reviews significant existing denoising methods based on Independent Component Analysis and concludes with the tabular Summary of denoising methods and their salient features / applications.

The Multi-objective Solid Transportation Problem (MSTP) refers to a special class of vectorminimum linear programming problems, in which constraints are all equality type and the objectives, are conflicting in nature. A generalization of multi-objective solid transportation problem, in which the supply, demand and capacity constraints are not only equality type but also of inequality type is considered. All methods either generate a set of non-dominated solution or find a compromise solution. In this paper, fuzzy programming technique is applied to solve multi-objective solid transportation problem. Special type of non-linear membership functions - Hyperbolic and Exponential are used to represent objective function into fuzzy environment. It gives an optimal compromise solution. The obtained result has been compared with the solution obtained by using a linear membership function. The method is illustrated with a numerical example.

This study presents a new visualization tool for classification of satellite imagery. Visualization of feature space allows exploration of patterns in the image data and insight into the classification process and related uncertainty. Visual Data Mining provides added value to image classifications as the user can be involved in the classification process providing increased confidence in and understanding of the results. In this study, we present a prototype visualization tool for visual data mining (VDM) of satellite imagery. The visualization tool is showcased in a classification study of highresolution imageries of Latur district in Maharashtra state of India.