基于案例推理的多准则综合评价

Case Based Reasoning for Multi Criteria Evaluation

案例推理是动态决策环境下求解不良结构问题的常用方法．本文把基于案例的推理方法运用于多准则综合评价中，扩展了传统数学模型的求解方式，文中详细叙述了基于案例的属性权重建立算法和相似性度量算法，并将该方法与神经网络模型作了全面比较，指出了存在的优缺点和今后的改进方向．

Case based reasoning is the most preferred method for uncertain decision in complex and dynamic situations. In this paper, we apply this method to the multi criteria evaluation to extend the functions of the traditional mathematical model. The algorithm for attributes weights and similarity computation are discussed. A comparison between our model and neural networks is also conducted.