Skip to main content
SpringerLink
Log in

Comparison of neural network configurations in the long-range forecast of southwest monsoon rainfall over India

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

The accurate long-range forecast of southwest rainfall can have manifold benefits for the country, from disaster mitigation and town planning to crop planning and power generation. In this paper, the rainfall has been modeled using artificial neural network (ANN) with different network configurations. Performance of these networks are compared with some results found in the literature. The networks have also been tested for the data outside the range of the trained data and compared with known results. The present network is found to be better in term of predictions than the previous results by others. Southwest monsoon rainfall over India for 6 years in advance has been predicted.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Farmer JD, Sidorowich JJ (1988) “Exporting chaos to predict the future and reduce noise”, LA-UR-88-901, theoretical division and centre for nonlinear studies. Los Alamos National Lab, Los Alamos

  2. Gadgil S, Srinivasan J, Nanjundiah R, Krishna Kumar K, Munot AA, Rupa Kumar K (2002) On forecasting the Indian summer monsoon: the intriguing season of 2002. Curr Sci 83:394–403

    Google Scholar 

  3. Goswami P, Srividya (1996) A novel neural network design for long range prediction of rainfall pattern. Curr Sci 70:447–457

    Google Scholar 

  4. Goswami P, Kumar P (1997) Experimental annual forecast of all-India mean summer monsoon rainfall for 1997 using a neural network model. Curr Sci 72:781–782

    Google Scholar 

  5. Rajeevan M, Pai DS, Dikshit SK, Kelkar RR (2004) IMD’s new operational models for long-range forecast of southwest monsoon rainfall over India and their verification for 2003. Curr Sci 86:422–431

    Google Scholar 

  6. Report : Newindpress.com, features—health and science, April 8, 2004. CSIR computer model forecast rainfall 2 yrs in advance

  7. Rumelhart DE, McClelland JL (1986) Parallel distributed processing. MIT Press, Cambridge

    Google Scholar 

Download references

Acknowledgments

The authors would like to thank Director, C.B.R.I., Roorkee for giving us permission to publish this paper. The authors also wish to thank the anonymous reviewer for the valuable suggestions.

Author information

Authors and Affiliations

  1. B.P.P.P. Division, Central Building Research Institute, Roorkee, 247 667, India

    Snehashish Chakraverty & Pallavi Gupta

Authors
  1. Snehashish Chakraverty
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pallavi Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Snehashish Chakraverty.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chakraverty, S., Gupta, P. Comparison of neural network configurations in the long-range forecast of southwest monsoon rainfall over India . Neural Comput & Applic 17, 187–192 (2008). https://doi.org/10.1007/s00521-007-0093-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-007-0093-y

Keywords

Search

Navigation