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针对多信息来源、多数据结构的复杂评价问题,对传统评价模式进行拓展并提出了泛综合评价的方法。泛综合评价理论主要为复杂评价信息的整合及求解提供支撑,具体而言主要采用构建信息融合框架的方式对不同类别与结构的多源信息进行整合,并通过随机模拟仿真的方法对信息融合框架的求解算法进行了探讨。由于信息融合框架中包含信息的复杂性增加了框架的求解成本,因而进一步分析了信息集成框架的简化求解算法,并通过算例的方式对信息集成框架简化求解算法的有效性进行了验证。简化求解算法的研究提升了泛综合评价在实际应用中的可操作性。“区域发展绩效的参与式评价”算例的构建,说明泛综合评价的理论为不同利益主体之间的民主决策提供了可能。本文的研究可为大数据背景下群体智慧的挖掘、民主决策的结果分析等实际应用问题提供理论和技术支撑。
In view of the complicated evaluation of multi-information sources and multi-data structures, the traditional evaluation mode is extended and a general evaluation method is proposed. The general evaluation theory mainly supports the integration and solution of complex evaluation information. In particular, the information fusion framework is mainly used to integrate multi-source information of different categories and structures. By means of stochastic simulation, The solution algorithm is discussed. Due to the complexity of the information contained in the information fusion framework, the solution cost of the framework is increased, so the simplified solution algorithm of the information integration framework is further analyzed. The validity of the simplified algorithm for information integration framework is verified by examples. The research of simplified solution algorithm enhances the operability of pan-general evaluation in practical application. The construction of the “Participatory Evaluation of Regional Development Performance” shows that the theory of generalized evaluation provides the possibility for democratic decision-making among different stakeholders. The research in this paper can provide theoretical and technical support for the practical application of the mining of group wisdom under the background of big data and the analysis of the result of democratic decision-making.