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【目的】在构建光伏项目投资风险监测模型的过程中,为了甄选面向互联网金融平台的大数据应用监测指标,尝试提出系统的甄选方案并结合实际案例进行验证。【方法】应用大数据监测模型,整合Solarbao平台多源异构数据,以专家判断为项目投资风险分析依据,运用CHAID决策树归纳多维监测指标组合,并运用R-Q型因子分析方法提炼识别投资风险的关键指标。【结果】得到8条监测光伏项目投资风险的指标组合和10项识别投资风险的关键指标。【局限】R-Q型因子分析中的专业指标有待进一步细分并形成动态更新机制。【结论】该甄选方案能够满足大数据监测模型对指标采集的要求,对投资者评估光伏项目风险、平台筛选合适项目以及监管部门排查该领域系统性风险具有借鉴意义。
【Objective】 In the process of constructing investment risk monitoring model of PV project, in order to select monitoring indicators of big data application for Internet financial platform, this paper attempts to propose a systematic selection scheme and verify with actual cases. 【Method】 By using big data monitoring model and integrating multiple sources and heterogeneous data of Solarbao platform, experts judged it as the basis of project investment risk analysis, using CHAID decision tree to summarize the combination of multi-dimensional monitoring indicators and using RQ-based factor analysis method to extract and identify investment risk Key indicators. 【Result】 Eight indicators combinations for monitoring the investment risk of PV projects and ten key indicators for identifying investment risks were obtained. [Limitations] The R-Q factor analysis of the professional indicators to be further subdivided and form a dynamic update mechanism. 【Conclusion】 This selection scheme can meet the requirements of indicator acquisition in big data monitoring model, which is of reference to investors in assessing risks of PV projects, screening appropriate projects on the platform and supervising regulatory agencies to investigate systemic risks in this area.