| 基于数据包络分析的统计预测模型有效性评价 |
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| 引用本文： | 毛晓敏,尚松浩.基于数据包络分析的统计预测模型有效性评价[J].水科学进展,2010,21(5):690-695. |
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| 作者姓名： | 毛晓敏 尚松浩 |
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| 作者单位： | 1.中国农业大学水利与土木工程学院, 中国农业水问题研究中心, 北京, 100083; |
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| 基金项目： | "十一五"国家科技支撑计划资助项目，教育部新世纪优秀人才支持计划资助项目，北京市重点学科"水文学及水资源"建设资助项目 |
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| 摘 要： | 统计预测模型是进行中长期水文预报的主要手段之一,在统计预测模型建模过程中面临的一个重要问题是如何从诸多待选模型中挑选出一个预测投入较低、预测精度较高的模型。针对这一多属性综合评价问题,提出了利用数据包络分析中的CCR模型进行水文统计预测模型综合评价的方法。模型的输入指标包括预测因子指标和模型参数指标,输出指标为模型精度评价指标,评价结果为模型的相对效率。作为典型案例,对参考作物腾发量预测的20个径向基函数网络模型的有效性进行了评价,结果表明该评价方法是可行的。模型中预测旬参考作物腾发量的关键因子是最高、最低温度,其次是风速,再次是日照时数;将预测时段所属的旬序号作为网络输入可显著提高模型预测精度和相对效率。
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| 关 键 词： | 预测模型 效率 评价 数据包络分析 腾发 径向基函数网络 |
| 收稿时间： | 2009-10-10 |
Assessment of the effectiveness of statistical forecasting models using data envelopment analysis |
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| MAO Xiao-min,SHANG Song-hao.Assessment of the effectiveness of statistical forecasting models using data envelopment analysis[J].Advances in Water Science,2010,21(5):690-695. |
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| Authors: | MAO Xiao-min SHANG Song-hao |
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| Institution: | 1.Center for Agricultural Water Research in China, College of Water Conservancy and Civil Engineering, China Agricultural University, Beijing 100083, China;2.State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China |
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| Abstract: | Statistical hydrological forecasting models have been widely used for the medium and long term hydrological forecasting.One major concern for these models is how to choose an appropriate one with less imput and higher precision.The Charnes,Cooper and Rhodes(CCR)model for data envelopment analysis is used here for the multi-attributes evaluation of these forecasting models.In the CCR model, the inputs include indexes for forecasting factors and model parameters,the outputs include precision indexes,and the evaluation result is the relative efficiency of each model compared with other models.This method is used to evaluate 20 models of radial basis function networks for forecasting reference evapotranspiration.Results show that the CCR model is feasible for this kind of multi-attributes evaluation of forecasting models.Key factors for forecasting reference evapotranspiration are identified,which are maxmium and minmium temperature,wind speed and sunshine hours.Moreover,the forecasting precision and relative efficiency of a network could be miproved significantly if the date was added as an input of the network. |
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| Keywords: | orecasting model efficiency evaluation data envelopment analysis evapotranspiration radial basis function networks |
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