| 引用本文: | 孔维娟,马荣华,段洪涛.结合温度因子估算太湖叶绿素a含量的神经网络模型.湖泊科学,2009,21(2):193-198. DOI:10.18307/2009.0206 |
| KONG Weijuan,MA Ronghua,DUAN Hongtao.The neural network model for estimation of chlorophyll-a with water temperature in Lake Taihu. J. Lake Sci.2009,21(2):193-198. DOI:10.18307/2009.0206 |
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| 摘要: |
| 神经网络方法估算复杂水体水质参数的优越性已经得到证实.基于太湖水体实测叶绿素a浓度,利用MODIS250m影像和反演得到的水温数据建立了估算太湖水体叶绿素a含量的两个单隐层BP神经网络模型:NN1模型不含温度因子、NN2模型包含温度因子,采用Levenberg-Marquardt算法训练网络,利用初期终止方法提高网络泛化能力,均取得了较高估算精度,其中包含温度因子的反演模型精度稍有提高,但不显著. |
| 关键词: 叶绿素a BP神经网络 MODIS 水温 太湖 |
| DOI：10.18307/2009.0206 |
| 分类号: |
| 基金项目:国家自然科学基金(40871168、40671138、40801137);国家科技支撑项目(2007BAC26B01)联合资助 |
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| The neural network model for estimation of chlorophyll-a with water temperature in Lake Taihu |
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KONG Weijuan1,2, MA Ronghua1, DUAN Hongtao1
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1.Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;2.Department of Geography Information Science, Nanjing University, Nanjing 210093, P. R. China
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| Abstract: |
| The advantage of neural network method for estimating water quality parameters of complex water body has been approved. Using in-situ measurement data of chlorophyll-a concentration, imageries of MODIS 250m and retrieval model of water temperature, we develop two single-hidden-layer BP neural network models for estimating chlorophyll-a in Lake Taihu: Model NN1 without temperature input and Model NN2 with temperature input. The training method is used by Levenberg-Marquardt algorithm, and the early-stage determinationin the modeling is used to improve generalization. The results show that: the estimation precision of the two models is high, in which the estimation precision of neural network input with temperature has been improved although the test is not significant. |
| Key words: Chlorophyll-a BP neural network MODIS water temperature Lake Taihu |
