Group decision-making based case retrieval and its application

The distribution of the case feature attribute weights directly affects the case retrieval result. Aim at improving the retrieval precision, a retrieval method is proposed based on group decision-making for optimizing the case feature attributes weights. Firstly, multiple groups of initial weights are obtained by genetic algorithm. Then, the multiple sets of retrieval results produced by these weights are optimized through group decision-making method, and the weights can be dynamic adjusted through the deviations between individual decision results and group result. The simulation results indicate that the proposed approach can fully excavate the potential knowledge of attribute weights and thus result in higher retrieval accuracy in a case-based reasoning system. The PID adjusting comparison experiment of typical two order delay system verifies the effectiveness of the new method.