基于模糊综合评价和神经网络的烟草配送车组评价模型

在综合研究烟草系统配送车组特征并结合现场实际调研的基础上,构建了烟草配送车组综合评价模型,提出了烟草配送车组综合评价指标体系。运用神经网络方法,基于用户满意度对于车组综合评价指标权重进行赋权训练,依据训练结果确定指标重要程度从而得到组合权重,建立了用户满意度对车组客观指标间的引导联系。考虑到丰富后的车组综合评价系统的多目标、多层次以及指标数据的模糊、不确定性等特点,采用模糊综合评价方法进行研究,并结合案例进行了实证分析,结果证明该指标体系更加全面且较好地反映了客户满意度水平。

Evaluation Model of Tobacco Distribution Fleet Based on Fuzzy Comprehensive Evaluation and Neural Network

In this paper,based on a comprehensive study of the characteristics of the distribution vehicle fleet of the tobacco commerce system and the result of a site investigation,we constructed the comprehensive evaluation model of the tobacco distribution vehicle fleet,as well as the corresponding comprehensive evaluation index system.Next,using the neural network method,we had a weight training to the indexes according to the level of user satisfaction,and further arrived at the combination weight of the indexes in light of their importance based on the training result,and established the guided connection between user satisfaction and the objective indexes of the vehicle fleet.At the end,taking into account such characteristics as the multiple objectives and layers of the evaluation system,and the fuzziness and uncertainty of the index data,we applied the fuzzy comprehensive evaluation method in a case study,the result of which proved the ability of the index system proposed in this paper to more comprehensively and better reflect the level of customer satisfaction about the distribution vehicle fleet.