Skip to main content
Springer Nature Link
Log in

Neural Network Algorithm Variants for Malaysian Weather Prediction

  • Conference paper
Soft Computing Applications and Intelligent Systems (M-CAIT 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 378))

Included in the following conference series:

  • 917 Accesses

Abstract

This paper studies the performance of a newly prepared time-series rainfall data by a previous researcher. The issues related are; (i) the large amount of data, and (ii) the accuracy of the prediction. In this study, the data set was obtained from Institute of Climate Change UKM, pre-processed using improved Symbolic Aggregate approximation (iSAX) and verified by experts. Five neural network algorithms were tested with the data set, namely standard Back-Propagation (BPNN), Back-Propagation with Momentum (BP with Mom), Quick-Propagation (QuickProp), Genetic Algorithm with neural network (GA-NN) and Particle Swarm Optimization with neural network (PSO-NN). The performances of these engines were measured according to the accuracy of prediction and the training time taken. The experimental results showed that while standard BPNN and PSO-NN achieved about the same accuracy prediction, PSO-NN is considered to be better as it showed a faster training time with acceptable prediction accuracy.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Zavala, V.M., Constantinescu, E.M., Anitescu, M.: Economic Impacts of Advance Weather Forecasting on Energy System Operations. In: IEEE PES, pp. 1–7 (2010)

    Google Scholar 

  2. Nguyen, V.G.N., Vo, T.T., Huynh, H.X., Drogoul, A.: On Weather Affecting to Brown Plant Hopper Invasion using an Agent-based Model. In: MEDES 2011, pp. 150–157 (2011)

    Google Scholar 

  3. Pielke Jr., R., Carbone, R.E.: Weather Impacts, Forecasts and Policy: An Integrated Perspective. Bulletin of American Meteorological Society, 393–403 (2002)

    Google Scholar 

  4. Li, C., Wang, Y., Liu, X.: Research on Natural Disaster Forecasting Data Processing and Visualization Technology. In: 4th International Congress on Image and Signal Processing, pp. 1775–1778 (2011)

    Google Scholar 

  5. Lee, R., Liu, J.: iJADE WeatherMAN: A Weather Forecasting System Using Intelligent Multiagent-Based Fuzzy Neuro Network. IEEE Transactions on Systems, Man, and Cybernatics - Part C: Applications and Reviews 34, 369–377 (2004)

    Article  Google Scholar 

  6. Isa, I.S., Omar, S., Saad, Z., Noor, N.M., Osman, M.K.: Weather Forecasting using Photovoltaic System and Neural Network. In: 2nd International Conference on Computational Intelligence, Communication Systems and Networks, pp. 96–100 (2010)

    Google Scholar 

  7. Rahman, I.I.A., Alias, N.M.A.: Rainfall Forecasting Using an Artificial Neural Network Model to Prevent Flash Floods. In: IEEE High Capacity Optical Networks and Enabling Technologies, pp. 323–328 (2011)

    Google Scholar 

  8. Saima, H., Jaafar, J., Belhaouari, S., Jillani, T.A.: Intelligent Methods for Weather Forecasting: A Review. In: National Postgraduate Conference (NPC 2011), pp. 1–6 (2011)

    Google Scholar 

  9. Yen, W.K.: A Study of Soft Computing Approach in Weather Forecasting. Masters Thesis, Universiti Teknologi Malaysia (2010)

    Google Scholar 

  10. Ahmed, A.M.A.: Pattern Discovery Algorithms for Time Series Data Mining. PhD Thesis, Universiti Kebangsaan Malaysia (2012)

    Google Scholar 

  11. Htike, K.K., Khalifa, O.O.: Rainfall Forecasting Model Using Focused Time-Delay Neural Networks. In: IEEE International Conference on Computer and Communication Engineering, pp. 1–6 (2010)

    Google Scholar 

  12. Abdul-Rahman, S., Hussein, Z.A.M., Bakar, A.A.: Velocity-based Reinitialisation Approach in Particle Swarm Optimization for Feature Selection. In: 11th International Conference on Hybrid Intelligent Systems, pp. 621–624 (2011)

    Google Scholar 

  13. Luo, F., Wu, C., Wu, J.: A Novel Neural Network Ensemble Model Based on Sample Reconstruction and Projection Pursuit for Rainfall Forecasting. In: IEEE Sixth International Conference on Natural Computation, pp. 32–35 (2010)

    Google Scholar 

  14. Biao, S., Li, Y.X., Yan, W., Li, P., Meng, X., Yu, X.H.: A Modified Particle Swarm Optimization and Radial Basis Function Neural Network Hybrid Algorithm Model and its Application. In: Global Congress on Intelligent Systems, pp. 134–138 (2009)

    Google Scholar 

  15. Tripathy, A.K., Mohapatra, S., Beura, S., Pradhan, G.: Weather Forecasting using ANN and PSO. International J. Scientific & Eng. Res. 2, 1–5 (2011)

    Google Scholar 

  16. Ahmed, M.A., Bakar, A.A., Hamdan, A.R.: Improved SAX Time Series Data Representation Based on Relative Frequency and K-Nearest Neighbour Algorithm. In: IEEE 10th International Conference on Intelligent Systems Designs and Applications, pp. 1320–1325 (2010)

    Google Scholar 

  17. Wardah, T., Kamil, A.A., Hamid, A.B.S., Maisarah, W.W.I.: Statistical Verification of Numerical Weather Prediction Models for Quantitative Precipitation Forecast. In: IEEE Colloquium on Humanities, Science and Engineering, pp. 88–92 (2011)

    Google Scholar 

  18. Hong, W.C.: Rainfall Forecasting by Technological Machine Learning Models. J. Applied Maths. and Comp. 200, 41–57 (2008)

    Article  MATH  Google Scholar 

  19. Wu, Y.K., Hong, J.S.: A Literature Review of Wind Forecasting Technology in the World. In: IEEE Power Tech, pp. 1–6 (2007)

    Google Scholar 

  20. Juneng, L., Tangang, F.T., Kang, H., Lee, W.J., Yap, K.S.: Statistical Downscaling Forecasts for Winter Monsoon Precipitation in using Multimodel Output Variables. J. Climate 23(11), 17–22 (2010)

    Article  Google Scholar 

  21. Gilleland, E., Ahijevych, D., Brown, B.G., Casati, B., Ebert, E.E.: Intercomparison of Spatial Forecast Verification Methods. J. American Meteorological Society 24(5), 1416–1430 (2009)

    Google Scholar 

  22. Negnevitsky, M.: Artificial Intelligence: A Guide to Intelligent Systems, 2nd edn. Addison Wesley, England (2005)

    Google Scholar 

  23. Luk, K.C., Ball, J.E., Sharma, A.: An Application of Artificial Neural Networks for Rainfall Forecasting. Mathematical and Computer Modelling 83, 683–693 (2001)

    Article  Google Scholar 

  24. Lai, L.L., Braun, H., Zhang, Q.P., Wu, Q., Ma, Y.N., Sun, W.C., Yang, L.: Intelligent Weather Forecast. In: Proceedings of the Third International Conference on Machine Learning and Cybernatics, pp. 4221–4216 (2004)

    Google Scholar 

  25. Philip, N.S., Joseph, K.B.: A Neural Network Tool for Analysing Trends in Rainfall. Computers and Geosciences 29, 215–223 (2003)

    Article  Google Scholar 

  26. Jareanpon, C., Pensuwon, W., Frank, R.J., Davey, N.: An Adaptive RBF Network Optimised using a Genetic Algorithm Applied to Rainfall Forecasting. In: International Symposium on Communications and Information Technologies, pp. 1005–1010 (2004)

    Google Scholar 

  27. He, J., Valeo, C.: Comparative Study of ANN versus Parametric Methods in Rainfall Frequency Analysis. J. Hydrologic Engineering ASCE 14(2), 172–184 (2009)

    Article  Google Scholar 

  28. Tan, P.N., Steinbach, M., Kumar, V.: Introduction to Data Mining. Pearson International Edition, US (2006)

    Google Scholar 

  29. Ju, Q., Yu, Z., Hao, Z., Ou, G., Zhao, J., Liu, D.: Division-based Rainfall-runoff Simulations with BP Neural Networks and Xinanjing Model. Neurocomputing 72, 2873–2883 (2009)

    Article  Google Scholar 

  30. Gullo, F., Ponti, G., Tagarelli, A., Greco, S.: A Time Series Representation Model for Accurate and Fast Similarity Detection. Pattern Recognition 42, 2998–3014 (2009)

    Article  MATH  Google Scholar 

  31. Lai, C.P., Chung, P.C., Tseng, V.S.: A Novel Two-Level Clustering Method for Time Series Data Analysis. Expert Systems with Applications, 6319–6326 (2010)

    Google Scholar 

  32. Chen, J., Moon, Y.S., Wog, M.F., Su, G.: Palmprint Authentication using a Symbolic Representation of Images. Image and Vision Computing 28, 343–351 (2010)

    Article  Google Scholar 

  33. Lavangnananda, K., Sawasdimongkol, P.: Capability of Classification of Control Chart Patterns Classifiers using Symbolic Representation Pre-processing and Evolutionary Computation. In: 23rd IEEE International Conference on Tools with Artificial Intelligence, pp. 1047–1052 (2011)

    Google Scholar 

  34. Yang, H., Meng, F.: Application of Improved SAX Algorithm to QAR Flight Data. In: 2012 International Conference on Applied Physics and Industrial Engineering, pp. 1406–1413 (2012)

    Google Scholar 

  35. Ahmed, M.A., Bakar, A.A., Hamdan, A.R., Abdullah, S.M.S., Jaafar, O.: Discovering Frequent Serial Episodes in Symbolic Sequences for Rainfall Dataset. In: 4th Conference on Data Mining and Optimization, pp. 121–126 (2012)

    Google Scholar 

  36. Wu, J., Chen, E.: A Novel Nonparametric Regression Ensemble for Rainfall Forecasting using Particle Swarm Optimization Technique Coupled with Artificial Neural Network. In: Yu, W., He, H., Zhang, N. (eds.) ISNN 2009, Part III. LNCS, vol. 5553, pp. 49–58. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  37. Kennedy, J., Spears, W.: Matching Algorithms to Problems: An Experimental Test of the Particle Swarm and Some Genetic Algorithms on the Multimodal Problem Generator. In: Evolutionary Computation Proceeding, pp. 78–83 (1998)

    Google Scholar 

  38. Fausett, L.: Fundamentals of Neural Network: Architecture, Algorithm and Applications. Prentice Hall Inc., New Jersey (1994)

    Google Scholar 

  39. Gill, J., Singh, B., Singh, S.: Training Back Propagation Neural Networks with Genetic Algorithm for Weather Forecasting. In: 8th International Symposium on Intelligent Systems and Informatics, pp. 465–469 (2010)

    Google Scholar 

  40. Fahlman, S.E.: An Empirical Study of Learning Speed in Back-Propagation Networks. In: CMU-CS, pp. 88–162 (1988)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Technology and Information Science, Universiti Kebangsaan Malaysia, 46300, Bangi, Selangor, Malaysia

    Siti Nur Kamaliah Kamarudin & Azuraliza Abu Bakar

Authors
  1. Siti Nur Kamaliah Kamarudin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Azuraliza Abu Bakar
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Faculty of Information Science & Technology, University Kebangsaan Malaysia, Bangi, Selangor, Malaysia

    Shahrul Azman Noah

  2. Center for Artificial Intelligence Technology (CAIT), Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor D. E, Malaysia

    Azizi Abdullah

  3. Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan, Malaysia

    Haslina Arshad , Zulaiha Ali Othman  & Zalinda Othman ,  & 

  4. School of Computer Science, FTSM, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan, Malaysia

    Azuraliza Abu Bakar

  5. Pattern Recognition Research Group, CAIT, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Shahnorbanun Sahran

  6. Faculty of Information Science & IT, National University of Malaysia, 43600, Bangi, Selangor, Malaysia

    Nazlia Omar

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kamarudin, S.N.K., Abu Bakar, A. (2013). Neural Network Algorithm Variants for Malaysian Weather Prediction. In: Noah, S.A., et al. Soft Computing Applications and Intelligent Systems. M-CAIT 2013. Communications in Computer and Information Science, vol 378. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40567-9_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40567-9_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40566-2

  • Online ISBN: 978-3-642-40567-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics