中文摘要：

为解决ASP平台下动态联盟由于规模复杂、功能目标多样而导致风险评价困难的问题,通过探索性因子分析方法对ASP平台下动态联盟的风险指标体系进行研究,将各种关系复杂的风险因素综合为几个核心因子,从而构建出合理的ASP平台下动态联盟的风险指标体系。在此指标体系基础上建立了相应的人工神经网络结构模型。为了最终评价的确定性,通过专家对各指标因素进行打分,实现了各指标因素的无量纲化处理,并将定性的风险因素定量化。利用神经网络的自学习和自适应能力对数据进行训练,最终得出风险评分结果。通过Matlab软件对模型进行了训练,验证了模型的有效性。

英文摘要：

In order to solve the problem with difficult appraisal of risk that is caused by scale compliexity and function goal variety of the dynamic alliance under ASP platform. This study carried on research to the risk index system of the dynamic alliance under ASP platform through the exploratory factor analytical method, syn- thesized various kinds of risk factors with complicated relation into key factors. Thus, the rational risk index system of the dynamic alliance under ASP platform structured out and corresponding artificial neural network structure model on the basis of the index system is set up. Thinking about the determinacy of final appraisal, experts are invited to give marks to every index factor, every index factor dimensioned is realized, the qualita- tive risk factors and is quantified. Since the neural network has been studied and adaptive capacity to train the data, the result of marking risk can be worked out. Finally, the model is verified validity in the way of training data by Matlab software.