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Fu, J., Tong, J., Wang, Q., et al. (2010) A Data Prediction Method under Small Sample Condition by Combining Neural Network and Grey System Methods. Proceedings of SPIE—The International Society for Optical Engineering, 7997, 79971E.
https://doi.org/10.1117/12.887370

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  • 标题: 基于组合预测模型的特高压工程造价预测Cost Forecasting of UHV Project Based on Combination Forecasting Model

    作者: 温卫宁, 郑燕, 赵昱宣, 卢艳超, 危雪林

    关键字: 特高压, 决策, 造价, 预测模型UHV, Decision, Project Cost, Forecasting Model

    期刊名称: 《Smart Grid》, Vol.6 No.6, 2016-12-12

    摘要: 特高压工程造价具有投资高、规模大等特点。特高压工程造价预测对提高特高压工程建设的经济效益,指导实际工程的决策和工程管理具有重要意义。首先,根据特高压工程的特点,分析特高工程造价预测思路,提出用多种造价预测方法构建预测模型。然后,根据各预测模型结果,用熵权法计算组合预测权重。由于各方法的局限性,又以特高压工程历史数据特点对组合预测权重进行了修正,得到最终造价组合预测模型。最后,以直流换流站工程和直流线路工程说明了本文组合预测模型的有效性。 UHV project is with high investment and large scale. The prediction of UHV project cost is of great significance to improve the economic benefits of UHV construction and to guide the decision and management of the actual project. Firstly, according to the characteristics of UHV project, this paper analyzes the cost forecasting method of UHV project, and puts forward a multi-cost-forecasting method to construct the forecasting models. Then, according to the results of each forecasting model, the Entropy Method is utilized to compute the prediction weight of each model. Due to the limitations of each method and the characteristics of historical data of UHV projects, the combination prediction weights of all used methods are modified to get the final cost combination forecasting model. Finally, the effectiveness of the combined forecasting model is illustrated by a DC Conversion Station Project and a DC Transmission Line Project.

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