Optimization Method for Case Attributes Weights Based on Group Cardinal Utility Method

The selection of the case feature attribute weights directly affects the case retrieval precision.According to the existing problem of optimizing attribute weights,a new method based on group decision-making thought for optimizing the case feature attribute weights is proposed in this paper.Multiple sets of initial feature attribute weights are first obtained by genetic algorithm.The multiple sets of weights by group cardinal utility method are then optimized,and the weights can be adaptively adjusted during the reasoning process to ascertain reasonable feature attribute weights.Simulation results show that the proposed approach can fully excavates the potential knowledge that exists in multiple sets of attribute weights and improves the retrieval precision of the case-based reasoning system.