| 水分敏感指标人工神经网络模型研究 |
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| 引用本文： | 王龙,李靖,郑勇.水分敏感指标人工神经网络模型研究[J].云南农业大学学报,2007,22(3):423-426. |
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| 作者姓名： | 王龙 李靖 郑勇 |
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| 作者单位： | [1]云南农业大学水资源与节水灌溉重点实验室,云南昆明650201 [2]云南省环境科学与工程创新基地,云南昆明650201 [3]元江水利水电勘查设计院,云南元江650320 |
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| 基金项目： | 云南省十五科技重点攻关课题（2002NG14）;云南省高校学术带头人基金项目. |
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| 摘 要： | 选用经度、纬度和土壤有效含水量、全生育期日平均参考作物腾发量作为输入因子，水分敏感指标作为输出因子，构建了一个具有二层隐含层的BP人工神经网络模型，利用湖北和广西的水稻试验数据作为样本对网络进行训练和检验。结果表明：模型具有较高的拟合精度和预测精度，能够用于缺乏试验数据的地区进行水分敏感指标的计算。
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| 关 键 词： | 水分敏感指标 人工神经网络 模型 模拟 |
| 文章编号： | 1004-390X（2007）03-0423-04 |
| 收稿时间： | 2006-4-19 |
| 修稿时间： | 2006-04-192006-07-20 |
Study on Artificial Neural Network Model of Water Sensitivity Index |
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| WANG Long,LI Jing,ZHENG Yong.Study on Artificial Neural Network Model of Water Sensitivity Index[J].Journal of Yunnan Agricultural University,2007,22(3):423-426. |
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| Authors: | WANG Long LI Jing ZHENG Yong |
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| Institution: | 1. Key Laboratory for Water Resource and Water-saving Irrigation, Y A U, Kunming 650201, China; 2. Innovation Center of Environment Science and Engineering of Yunnan, Kunming 650201, China; 3. Yuanjiang Institute of Water Resources and Hydropower Engineering Investigation and Design, Yuanjiang 650320,China |
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| Abstract: | Based on analyzing effected factors of water sensitivity index, by using latitude, longitude, ETo^- and effective soil moisture as input and water sensitivity index output, a BP artificial neural network structure containing two hidden layers is established. The data of Hubei and Guangxi is used as sample to train and test the effective degree of the given model. The results indicate that the artificial neural network model for water sensitivity index of the fitting precision and the predicting precision are satisfactory, it is capable of simulating the water sensitivity index in area lack of data. |
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| Keywords: | water sensitivity index artificial neural network model simulation |
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