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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:NI Qing-wei,YE Ren-zhen,YANG Feng-lin,LEI Kun.Evolution algorithm for water storage forecasting response to climate change with little data sets:the Wolonghu Wetland,China[J].Journal of Harbin Institute Of Technology(New Series),2011,18(2):127-133.DOI:10.11916/j.issn.1005-9113.2011.02.025.
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Evolution algorithm for water storage forecasting response to climate change with little data sets:the Wolonghu Wetland,China
Author NameAffiliation
NI Qing-wei School of Environmental & Biological Science & Technology,Dalian University of Technology,Dalian 116024,China
Chinese Research of Enviromental Sciences,Beijing 100012,China 
YE Ren-zhen Huazhong Agricultral University,Wuhan 430070,China 
YANG Feng-lin Chinese Research of Enviromental Sciences,Beijing 100012,China 
LEI Kun Chinese Research of Enviromental Sciences,Beijing 100012,China 
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.
Key words:  water storage  little data set  evolution algorism  Wolonghu wetland
DOI:10.11916/j.issn.1005-9113.2011.02.025
Clc Number:X37
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