Based On The Correlation Of Multi-attribute Decision-making And Clustering Method Research

Fuzzy Mathematics and Grey System Theory are both effective tools to deal with incomplete, imprecise and uncertain information ,In this paper, through the two effective theories combination as an new useful tool to solve multi-attribute decision-making as the main object; as the knowledge acquisition for the purpose also analysis the evaluation of evidence. Study the uncertainty of the multi-attribute decision-making grey correlation degree and cluster analysis of the theory and methods. Are as follows:Firstly, introduced the basic fundamental research and the nature of the concept of both--fuzzy mathematics and the grey system theory, due to the complexity of objective things, uncertainty and ambiguity of human thinking, from two complementary and integration to deal with uncertainty and the need for a great reality.Secondly, Study the basic concepts, theorems , fundamental nature and the computing formula of the interval number. Since the self-divide and self- minus of interval numbers these two theorems to study the characteristics of the property value of interval number of decision-making objects and ideal correlation between the relative and absolute correlation, which sort of decision-making and select of the best target.Finally, research the Grey ISODATA Clustering method based on interval number for the decision-making objects of multi-attribute decision-making dynamic clustering analysis methods, can be refined knowledge and make the best decision-making.The article research in a new field that combination the both fuzzy mathematics and the grey system theory to deal with the uncertainties, for further study the issue of multi-attribute decision-making and decision-making object linkage method of clustering to provide a broader thought.