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Advances in Atmospheric Sciences

, Volume 18, Issue 5, pp 950–958 | Cite as

Forecasting Monsoon Precipitation Using Artificial Neural Networks

  • Xiaodan Wu
  • Cao Hongxing
  • Andrew Flitman
  • Wei Fengying
  • Feng Guolin
Article

Abstract

This paper explores the application of Artificial Intelligent (AI) techniques for climate forecast. It presents 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 corresponding area one year, five-year, and ten-year forward respectively. Performances of the models have been validated using a 1new1 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.

Key words

Forecasting Monsoon precipitation Artificial intelligent technique Artificial neural networks 

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Copyright information

© Advances in Atmospheric Sciences 2001

Authors and Affiliations

  • Xiaodan Wu
    • 1
  • Cao Hongxing
    • 2
  • Andrew Flitman
    • 1
  • Wei Fengying
    • 2
  • Feng Guolin
    • 2
  1. 1.School of Business Systems, Faculty of Information TechnologyMonash UniversityAustralia
  2. 2.Chinese Academy of Meteorological SciencesBeijingChina

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