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Study on Cost Forecast Method of Power Projects Based on Data Mining Technology

机译:基于数据挖掘技术的电力项目造价预测方法研究

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摘要

Based on cost data of certain zone history power transmission line projects, applying data mining technology including relative analysis, clustering analysis and support vector machine theory, one kind of new cost forecast methods of power projects is presented. Firstly, applying relative analysis and partial correlation analysis in SPSS15.0 software package, cost forecast index system is built after simplifying technical conditions of power projects. Next, using, clustering analysis, noise information of cost data of history projects is deleted. At last, using support vector machine theory, cost forecast model of power projects is designed. Simulation results of real power transmission line projects in Matlab7.0 software package show such model is valid and feasible.
机译:基于某区域历史输电线路工程造价数据,运用相关分析,聚类分析和支持向量机理论等数据挖掘技术,提出了一种新型的电力工程造价预测方法。首先,在SPSS15.0软件包中应用相对分析和偏相关分析,在简化电力项目技术条件的基础上,建立了成本预测指标体系。接下来,使用聚类分析,删除历史项目的成本数据的噪声信息。最后,基于支持向量机理论,设计了电力项目成本预测模型。 Matlab7.0软件包对实际输电线路工程的仿真结果表明,该模型是有效可行的。

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