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为了降低Web服务评价指标数据中人为主观因素的不确定性?服务提供商服务质量(QoS)的不确定性和确保指标项权重准确性,提出一种Web服务动态评估模型,运用灰色系统理论(GST)中的灰色处理方法对人为主观评分数据进行模糊化处理.同时,Web服务的主客观因子权重分别采用层次分析法(AHP)和改进的熵值赋权法计算,将主客观的权重进行组合计算综合权重,该模型具有反馈机制,通过QoS监测中心修正服务提供商提供的QoS值,能够自适应服务的动态变化.最后,仿真实验验证了本文所提出的评估模型不仅能适应动态变化的环境,而且能够保证用户选择服务的实际质量,克服了评价中出现的个体差异、恶意评价,实验结果表明,所提出的服务评估模型与选择策略具有可行性和实用性.
In order to reduce the uncertainty of human subjective factors in Web service evaluation index data, the uncertainty of QoS of service provider and the weight accuracy of index items, a dynamic evaluation model of Web service is proposed. By using gray system theory GST), the subjective scoring data of people are fuzzified.At the same time, the weight of subjective and objective factors of Web service is calculated by analytic hierarchy process (AHP) and improved entropy weighting method Combined with the calculation of comprehensive weight, this model has a feedback mechanism, which can adaptively adapt to the dynamic changes of services by modifying the QoS values provided by service providers through QoS monitoring center.Finally, the simulation results verify that the proposed evaluation model can not only adapt to dynamic changes Environment, but also can guarantee the actual quality of the service that the user chooses. It overcomes the individual differences and malicious evaluations that appear in the evaluation. The experimental results show that the proposed service evaluation model and the selection strategy are feasible and practical.