| 基于支持向量机的水资源可持续利用评价 |
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| 引用本文： | 卢敏 张展羽. 基于支持向量机的水资源可持续利用评价[J]. 水电能源科学, 2005, 23(5): 18-21 |
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| 作者姓名： | 卢敏 张展羽 |
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| 作者单位： | 1. 河海大学,现代农业工程系,江苏,南京,210098;云南农业大学,水电与建筑学院,云南,昆明,650201
2. 河海大学,现代农业工程系,江苏,南京,210098 |
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| 摘 要： | 针对水资源可持续利用评价方法的不足,提出了基于支持向量机的水资源可持续利用评价的新方法,并对汉中和淮河地区进行了实例应用;最后将基于支持向量机的评价结果,与人工神经网络和SP方法的评价结果进行对比,结果表明新方法模型简单、实用性强.
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| 关 键 词： | 水资源 可持续利用 支持向量机 评价 神经网络 |
| 文章编号： | 1000-7709（2005）05-0018-04 |
| 收稿时间： | 2005-09-05 |
| 修稿时间： | 2005-09-05 |
On Assessment of Sustainable Development Level of Regional Water Resource Based on Support-Vector-Machine |
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| LU Ming. On Assessment of Sustainable Development Level of Regional Water Resource Based on Support-Vector-Machine[J]. International Journal Hydroelectric Energy, 2005, 23(5): 18-21 |
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| Authors: | LU Ming |
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| Abstract: | In the light of dissatifaction of existing sustainable developmental level assessment methods of regional water resource(SDLRWR),an new assessment model based on support-vector-machine (SVM)was put forward and applied to assess the SDLRWR of Hanzhong and Huaihe regions. By contrast with artificial neural networks and Shepard(SP) method,its results show that the presented model was practical and convenient for use. It is feasible to use the model for assessment and decision-making of regional water resources. |
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| Keywords: | water resource sustainable development level support-vector-machine assessment artificial neural networks |
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