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基于SVM 的海上风电项目运行期风险评价
引用本文:李 静,谢珍珍,陈小波.基于SVM 的海上风电项目运行期风险评价[J].工程管理学报,2013,0(4):51-55.
作者姓名:李 静  谢珍珍  陈小波
作者单位:1,2. 大连理工大学 建设工程学部;3. 东北财经大学 投资工程管理学院
摘    要:海上风电项目投资成本高、运行环境复杂,为了有效预防控制其运行期风险,降低风险损失,提出了基于SVM(支持向量机)的海上风电项目运行期风险评价方法。在建立海上风电项目运行期风险评价指标的基础上,运用支持向量机理论构建海上风电项目运行期风险评价模型,通过具体项目数据分析其预测准确性。通过实证分析表明,在实际项目风险评价过程中,支持向量机的方法比传统评价方法更便捷、精确度更高,能够为海上风电项目运行期风险管理提供可靠依据。

关 键 词:海上风电项目  风险评价  支持向量机

Risk Evaluation on the Operation Period of OffshoreWind Power Projects Based on Support Vector Machine
LI Jing,XIE Zhen-zhen,CHEN Xiao-bo.Risk Evaluation on the Operation Period of OffshoreWind Power Projects Based on Support Vector Machine[J].Journal of Engineering Management,2013,0(4):51-55.
Authors:LI Jing  XIE Zhen-zhen  CHEN Xiao-bo
Affiliation:1,2. Faculty of Infrastructure Engineering,Dalian University of Technology; 3. School of Investment Project Management,Dongbei University of Finance and Economics
Abstract:In view of the complex running environment and the high investment cost of offshore wind power projects,a riskevaluation method based on SVM (support vector machine) has been proposed to prevent and control risks and reduce the lossescaused by risks in the operation period. Based on the characteristic of the projects’ risk, this paper proposes a risk evaluation modelfor offshore wind power projects using support vector machine, and analyses the forecast accuracy of the model through the specificproject data. Case study shows that the SVM method has higher accuracy and is more convenient than the traditional evaluationmethod, and provides basis for the risk evaluation of offshore wind project.
Keywords:offshore wind power projects  risk evaluation  support vector machine
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