基于前景理论和TOPSIS的新能源大数据服务项目综合评价研究

Renjie Chen, Xiaotao Peng, Huaqu Li, Shouwen Liu, Jun Yang, Xuzhu Dong
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引用次数: 1

摘要

本文从新能源大数据服务的目的和需求出发,从经济、技术、环境效益和社会服务四个方面构建了综合评价新能源大数据服务运行效率的综合评价指标体系。同时,利用最小差别信息原则,研究了基于改进层次分析和熵的综合赋权方法。其次,针对基于指标的决策综合评价中决策者的主观风险倾向可能影响结果的不足,引入了前景理论。考虑到投资者的有限理性和风险评估,结合前景理论和TOPSIS方法,进一步提出了利用新能源大数据服务项目综合效率评估结果对最优场景进行排序的方法。最后,通过仿真验证了综合效益评价指标体系和评价方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Comprehensive Evaluation for New Energy Big Data Service Project based on Prospect Theory and TOPSIS
This paper from considering the purpose and demand of new energy big data service, the comprehensive evaluation index system for comprehensively evaluating the operational efficiency of new energy big data service is constructed from four aspects of economy, technology, environmental benefits and social services. In the same time, the comprehensive empowerment method based on improved hierarchical analysis and entropy is also studied using the principle of minimum discriminatory information. Secondly, to address the shortcoming that the subjective risk tendency of decision makers probably takes impact on the results of the index-based comprehensive evaluation of decision-making, this paper introduces the prospect theory. Considering the limited rationality of investors and risk assessment, the prospect theory and TOPSIS method are combined to further propose the method which uses the results of the comprehensive efficiency assessment of new energy big data service projects to rank the optimal scenarios. Finally, the effectiveness of both the comprehensive benefit evaluation index system and evaluation method is verified by simulation.
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