| Forecasting Monsoon Precipitation Using Artificial Neural Networks |
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| 作者姓名： | Xiaodan Wu Cao Hongxing Andrew Flitman Wei Fengying Feng Guolin |
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| 作者单位： | Xiaodan Wu，Cao Hongxing Andrew Flitman，Wei Fengying and Feng Guolin School of Business Systems，Faculty of Information Technology，Monash University，Australia Chinese Academy of Meteorological Sciences，Beijing 100081 |
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| 摘 要： | This paper explores the application of Artificial Intelligent (AI) techniques for climate forecast. It pres ents a study on modelling the monsoon precipitation forecast by means of Artificial Neural Networks (ANNs). Using the historical data of the total amount of summer rainfall over the Delta Area of Yangtze River in China, three ANNs models have been developed to forecast the monsoon precipitation in the corre sponding area one year, five-year, and ten-year forward respectively. Performances of the models have been validated using a ＇new＇ data set that has not been exposed to the models during the processes of model development and test. The experiment results are promising, indicating that the proposed ANNs models have good quality in terms of the accuracy, stability and generalisation ability.
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Forecasting Monsoon Precipitation Using Artificial Neural Networks |
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| Xiaodan Wu,Cao Hongxing,Andrew Flitman,Wei Fengying,Feng Guolin.Forecasting Monsoon Precipitation Using Artificial Neural Networks[J].Advances in Atmospheric Sciences,2001,18(5):950-958. |
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| Authors: | Xiaodan Wu Cao Hongxing Andrew Flitman Wei Fengying and Feng Guolin |
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| Institution: | School of Business Systems, Faculty of Information Technology, Monash University, Australia,Chinese Academy of Meteorological Sciences, Beijing 100081,School of Business Systems, Faculty of Information Technology, Monash University, Australia,Chinese Academy of Meteorological Sciences, Beijing 100081,Chinese Academy of Meteorological Sciences, Beijing 100081 |
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| Abstract: | This paper explores the application of Artificial Intelligent (AI) techniques for climate forecast. It pres- ents a study on modelling the monsoon precipitation forecast by means of Artificial Neural Networks (ANNs) Using the historical data of the total amount of summer rainfall over the Delta Area of Yangtze River in China, three ANNs models have been developed to forecast the monsoon precipitation in the corre- sponding atea one year. five-year, and ten-year forward respectively. Performances of the models have been validated using a 'new' data set that has not been exposed to the models during the processes of model development and test. The experiment results are promising, indicating that the proposed ANNs models have good quality in terms of the accuracy, stability and generalisation ability. |
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| Keywords: | Forecasting Monsoon precipitation Artificial intelligent technique Artificial neural networks |
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