节点文献

Evolution algorithm for water storage forecasting response to climate change with little data sets:the Wolonghu Wetland,China

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 尼庆伟叶人珍杨凤林雷坤

【Author】 NI Qing-wei 1,2,YE Ren-zhen3,YANG Feng-lin1,LEI Kun2(1.School of Environmental & Biological Science & Technology,Dalian University of Technology,Dalian 116024,China;2.Chinese Research of Enviromental Sciences,Beijing 100012,China;3.Huazhong Agricultral University,Wuhan 430070,China)

【机构】 School of Environmental & Biological Science & Technology,Dalian University of TechnologyChinese Research of Enviromental SciencesHuazhong Agricultral University

【摘要】 An attempt of applying a novel genetic programming(GP) technique,a new member of evolution algorithms,has been made to predict the water storage of Wolonghu wetland response to the climate change in northeastern part of China with little data set.Fourteen years(1993-2006) of annual water storage and climatic data set of the wetland were taken for model training and testing.The results of simulations and predictions illustrated a good fit between calculated water storage and observed values(MAPE=9.47,r=0.99).By comparison,a multilayer perceptron(MLP)(a popular artificial neural network model) method and a grey model(GM) with the same data set were applied for performances estimation.It was found that GP technique had better performances than the other two methods both in the simulation step and predicting phase and the results were analyzed and discussed.The case study confirmed that GP method is a promising way for wetland managers to make a quick estimation of fluctuations of water storage in some wetlands under condition of little data set.

【Abstract】 An attempt of applying a novel genetic programming(GP) technique,a new member of evolution algorithms,has been made to predict the water storage of Wolonghu wetland response to the climate change in northeastern part of China with little data set.Fourteen years(1993-2006) of annual water storage and climatic data set of the wetland were taken for model training and testing.The results of simulations and predictions illustrated a good fit between calculated water storage and observed values(MAPE=9.47,r=0.99).By comparison,a multilayer perceptron(MLP)(a popular artificial neural network model) method and a grey model(GM) with the same data set were applied for performances estimation.It was found that GP technique had better performances than the other two methods both in the simulation step and predicting phase and the results were analyzed and discussed.The case study confirmed that GP method is a promising way for wetland managers to make a quick estimation of fluctuations of water storage in some wetlands under condition of little data set.

【基金】 Sponsored by the National Basic Research Program of China(Grant No. 2006CB403302);the National Education Ministry foundation of China(Grant No.705011);the National Special Science and Technology Program Water Pollution Control and Treatment (Grant No.2009ZX07526-006,2008AX07208-001)
  • 【文献出处】 Journal of Harbin Institute of Technology ,哈尔滨工业大学学报(英文版) , 编辑部邮箱 ,2011年02期
  • 【分类号】X37
  • 【被引频次】1
  • 【下载频次】68
节点文献中: 

本文链接的文献网络图示:

本文的引文网络