Abstract:

Taking into account the correlation among different indexes as well as the influences of both different dimensions and differences of importance on effect of decisions, this paper deals with improving traditional grey target decision methods with the approach of weighted Mahalanobis distance and discusses the property of the improved grey target method. The results indicate that the improved grey target could meet the invariance of effect samples after nonsingular linear transformation caused by clout distance; the weighted Mahalanobis distance is just the weighted Euclidean distance when there is no correlation among observed indexes, which avoids correlation of decision indexes, influences of different dimension and differences of importance on effect of decisions, and the incompatibility of grey target transformation. Finally, the effectiveness and availability of the model are proved by a real case in point.