Research Output
A survey on rainfall forecasting using artificial neural network
  Rainfall has a great impact on agriculture and people’s daily travel, so accurate prediction of precipitation is well worth studying for researchers. Traditional methods like numerical weather prediction (NWP) models or statistical models can’t provide satisfied effect of rainfall forecasting because of nonlinear and dynamic characteristics of precipitation. However, artificial neural network (ANN) has an ability to obtain complicated nonlinear relationship between variables, which is suitable to predict precipitation. This paper mainly introduces background knowledge of ANN and several algorithms using neural network applied to precipitation prediction in recent years. It is proved that neural network can greatly improve the accuracy and efficiency of prediction.

  • Type:


  • Date:

    04 May 2018

  • Publication Status:


  • DOI:


  • ISSN:


  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    005.4 Systems programming and programs

  • Funders:

    Edinburgh Napier Funded


Liu, Q., Zou, Y., Liu, X., & Linge, N. (2019). A survey on rainfall forecasting using artificial neural network. International Journal of Embedded Systems, 11(2), 240-249.



Rainfall, prediction, precipitation forecasting, artificial neural network, ANN, nonlinear relationship, training algorithms, embedded systems,

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