| 主/客观证据融合模型在洪水预测研究中的应用 |
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| 引用本文： | 吴蔚,王道席. 主/客观证据融合模型在洪水预测研究中的应用[J]. 计算机工程与应用, 2006, 42(12): 197-199,216 |
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| 作者姓名： | 吴蔚 王道席 |
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| 作者单位： | 浙江水利水电专科学校,杭州,310018;水利部黄河水利委员会,郑州,450003 |
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| 基金项目： | 科技部科研项目;浙江省水利厅资助项目 |
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| 摘 要： | 文章提出了BP神经网络联合与DS证据推理相融合的模型,实现了多个领域不同层次的全部主/客观证据的特征级融合,还实现了多个模型的优势互补。解决了单一模型洪水预测问题存在的算法复杂度高,分类准确率低等问题。通过实验得出,主/客观证据融合方法不仅提高了12%的分类精度,还降低了算法的时间复杂度。
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| 关 键 词： | 洪水预测主/客观证据融合 BP神经网络 DS证据理论 |
| 文章编号： | 1002-8331-（2006）12-0197-03 |
| 收稿时间： | 2005-11-01 |
| 修稿时间： | 2005-11-01 |
Application of Subjective and Objective Evidences Fusion Model in Study of Flood Prediction |
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| Wu Wei,Wang Daoxi. Application of Subjective and Objective Evidences Fusion Model in Study of Flood Prediction[J]. Computer Engineering and Applications, 2006, 42(12): 197-199,216 |
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| Authors: | Wu Wei Wang Daoxi |
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| Affiliation: | 1.Zhejiang Water Conservancy and Hydropower College,Hangzhou 310018; 2.Yellow River Conservancy Commission,Zhengzhou 450003 |
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| Abstract: | The paper presents a model by combining BP neural network and DS evidential reasoning,which not only achieves the feature level fusion of all subjective and objective evidences in various domains and layers,but also makes distinct models complement each other.The model solves these problems such as high complexity of algorithms and low accuracy rate of classifications lie in the flood prediction using single models.By the experiment,thls method improves classification precision by 12 percent and reduces the time complexity of algorithm. |
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| Keywords: | flood prediction subjective and objective evidences fusion BP Neural Network DS evidential theory |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
