| 基于SCE-UA算法的多模式降雨集成预报技术研究 |
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| 引用本文： | 钟,伟,朱从飞,张卫国,黄,峰.基于SCE-UA算法的多模式降雨集成预报技术研究[J].宁波大学学报(理工版),2018,0(6):27-31. |
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| 作者姓名： | 钟 伟 朱从飞 张卫国 黄 峰 |
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| 作者单位： | (1.宁波市水利水电规划设计研究院, 浙江 宁波 315192; 2.河海大学 水文水资源学院, 江苏 南京 210098) |
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| 摘 要： | 高精度的降雨预报对于防汛决策具有重要指导意义. 以中国气象局GRAPES_MESO模式、中国气象局T639模式、美国国家环境预报中心GFS模式和上海区域中尺度SMS-WARMS模式为基础, 采用SCE-UA算法估计各预报模式权重系数, 通过加权平均建立多模式降雨集成预报, 并以宁波市2016年8月1日至2016年10月31日和2017年9月1日至2017年11月30日的降雨过程为例, 从均方根误差、相关系数、TS评分等多个方面分析集成预报的预报效果. 结果表明: 基于SCE-UA算法的多模式降雨集成预报的预报效果不仅优于各单一预报模式, 而且优于遗传算法和BP神经网络集成预报, 表现出较好的适用性.
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| 关 键 词： | SCE-UA算法 多模式集成预报 降雨预报 |
ulti-model integrated precipitation forecast based on SCE-UA algorithm |
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| ZHONG Wei,ZHU Cong-fei,ZHANG Wei-guo,HUANG Feng.ulti-model integrated precipitation forecast based on SCE-UA algorithm[J].Journal of Ningbo University(Natural Science and Engineering Edition),2018,0(6):27-31. |
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| Authors: | ZHONG Wei ZHU Cong-fei ZHANG Wei-guo HUANG Feng |
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| Affiliation: | ( 1.Ningbo Hydraulic Waterpower Planning Designing Research Institution, Ningbo 315192, China; 2.College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China ) |
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| Abstract: | Predicting with high-precision precipitation is a key for flood control decision-making. Based on the data collected from GRAPES_MESO and T639 of China Meteorological Administration, GFS of National Centers for Environmental Prediction and SMS-WARMS of Shanghai, SCE-UA algorithm is used to estimate the weighting of each forecast model. With the weighting estimated, the multi-model integrated precipitation is established. Using the data from Ningbo precipitation occurrences between August 1, 2016 and October 31, 2016, as well as from September 1, 2017 to November 30, 2017, the integrated forecast result is analyzed from a variety of indices such as root-mean-square error, correlation coefficient and TS grade. The result indicates that the integrated forecast based on SCE-UA is more accurate and applicable than not only those from individual forecast models but also those based on genetic algorithm and BP integrated forecast models. |
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| Keywords: | SCE-UA algorithm multi-model integrated forecast precipitation forecast |
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