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	Application of artificial neural networks to the prediction of dust storms in Northwest China
	Huang M.
	2006
关键词	artificial neural net works dust storms Northwest China regression model ozone concentrations wind erosion models lakes
英文摘要	Artificial neural networks (ANN) are non-linear mapping structures analogous to the functioning of the human brain. In this study, we take the ANN approach to model and predict the occurrence of dust storms in Northwest China, by using a combination of daily mean meteorological measurements and dust storm occurrence. The performance of the ANN model in simulating dust storm occurrences is compared with a stepwise regression model. The correlation coefficients between the observed and the estimated dust storm occurrences obtained from the neural network procedure are found to be significantly higher than those obtained from the regression model with the same input data. The prediction tests show that the ANN models used in this study have the potential of forecasting dust storm occurrence in Northwest China by using conventional meteorological variables. (C) 2006 Elsevier B.V. All rights reserved.
出处	Global and Planetary Change
卷	52
期	1-4
页	216-224
收录类别	SCI
语种	英语
ISSN号	0921-8181
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/23803]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Huang M.. Application of artificial neural networks to the prediction of dust storms in Northwest China. 2006.

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