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Predictive Analytics for Weather Forecasting Using Back Propagation and Resilient Back Propagation Neural Networks

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New Paradigm in Decision Science and Management

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1005))

Abstract

Weather can be elucidated as the appearance of atmosphere for a short span of time for a specific place. Weather an important factor in our day-to-day lives and also the one that controls how and what people should do. For researchers and scientists, weather has been the most demanding task. The practice of technology that has been practiced to presume the conditions of atmosphere for a given area at a specific time is weather forecasting. Rationally accurate forecasts are obtained because of modern weather forecasting methods that involve computer models, observations and information about current patterns, and trends. Due to the presence of nonlinearity in climatic data, neural networks have been the satisfactory for prediction of weather. An algorithm based on artificial neural networks is used for predicting the future weather as the artificial neural network (ANN) package supports a number of learning or training algorithms. The benefits of using artificial neural networks for predicting the weather have been presented in this paper. In this paper, weather predictions are made by building training and testing datasets with the usage of learning algorithms back propagation and resilient back propagation.

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References

  1. Maqsood, I., Khan, M.R., Abraham, A.: An ensemble of neural networks for weather forecasting. Neural Comput. Appl. 13(2), 112–122 (2004)

    Article  Google Scholar 

  2. Maqsood, I., Khan, M.R., Huang, G.H., Abdalla, R.: Application of soft computing models to hourly weather analysis in southern Saskatchewan, Canada. Eng. Appl. Artif. Intell. 18(1), 115–125 (2005)

    Article  Google Scholar 

  3. Kumari, A., Alankar, B., Grover, J.: Feature level fusion of multispectral palmprint. Int. J. Comput. Appl. (0975-8887) 144(3) (2016)

    Article  Google Scholar 

  4. Mahdi, O.A., Alankar, B.: Wireless controlling of remote electrical device using android smartphone. IOSR J. Comput. Eng. (IOSR-JCE) 16(3), 23–27 (2014). e-ISSN: 2278-0661

    Google Scholar 

  5. Donate, J.P., Li, X., Sánchez, G.G., de Miguel, A.S.: Time series forecasting by evolving artificial neural networks with genetic algorithms, differential evolution and estimation of distribution algorithm. Neural Comput. Appl. 22(1), 11–20 (2013)

    Article  Google Scholar 

  6. Mellit, A., Pavan, A.M., Benghanem, M.: Least squares support vector machine for short-term prediction of meteorological time series. Theoret. Appl. Climatol. 111(1–2), 297–307 (2013)

    Article  Google Scholar 

  7. Shank, D.B., Hoogenboom, G., McClendon, R.W.: Dewpoint temperature prediction using artificial neural networks. J. Appl. Meteorol. Climatol. 47(6), 1757–1769 (2008)

    Article  Google Scholar 

  8. Chaudhuri, S., Chattopadhyay, S.: Neuro-computing based short range prediction of some meteorological parameters during the pre-monsoon season. Soft. Comput. 9(5), 349–354 (2005)

    Article  Google Scholar 

  9. Hayati, M., Mohebi, Z.: Temperature forecasting based on neural network approach. World Appl. Sci. (2007)

    Google Scholar 

  10. Devi, C.J., Reddy, B.S.P., Kumar, K.V., Reddy, B.M., Nayak, N.R.: ANN approach for weather prediction using back propagation. Int. J. Eng. Trends Technol. 3(1), 19–23 (2012)

    Google Scholar 

  11. Paras, S.M., Kumar, A., Chandra, M.: A feature based neural network model for weather forecasting. In: Proceedings of World Academy of Science, Engineering and Technology, pp. 66–74 (2007)

    Google Scholar 

  12. Singh, S., Bhambri, P., Gill, J.: Time series based temperature prediction using back propagation with genetic algorithm technique. Int. J. Comput. Sci Issues (IJCSI) 8(5), 28 (2011)

    Google Scholar 

  13. Abhishek, K., Kumar, A., Ranjan, R., Kumar, S.: A rainfall prediction model using artificial neural network. In: Control and System Graduate Research Colloquium (ICSGRC), 2012 IEEE, pp. 82–87. IEEE (July, 2012)

    Google Scholar 

  14. Sawaitul, S.D., Wagh, K.P., Chatur, P.N.: Classification and prediction of future weather by using back propagation algorithm-an approach. Int. J. Emerg. Technol. Adv. Eng. 2(1), 110–113 (2012)

    Google Scholar 

  15. Srinivasulu, S., Sakthivel, P.: Extracting spatial semantics in association rules for weather forecasting image. In: Trendz in Information Sciences & Computing (TISC), 2010, pp. 54–57. IEEE (December, 2010)

    Google Scholar 

  16. Naik, A.R., Pathan, S.K.: Weather classification and forecasting using back propagation feed-forward neural network. Int. J. Sci. Res. Publ. 2(12), 1–3 (2012)

    Google Scholar 

  17. Geetha, G., Selvaraj, R.S.: Prediction of monthly rainfall in Chennai using back propagation neural network model. Int. J. Eng. Sci. Technol. 3(1) (2011)

    Google Scholar 

  18. Malik, P., Singh, S., Arora, B.: An effective weather forecasting using neural network. Int. J. Emerg. Eng. Res. Technol. 2(2), 209–212 (2014)

    Google Scholar 

  19. Al-Matarneh, L., Sheta, A., Bani-Ahmad, S., Alshaer, J., Al-Oqily, I.: Development of temperature-based weather forecasting models using neural networks and fuzzy logic. Int. J. Multimedia Ubiquit. Eng. 9(12), 343–366 (2014)

    Article  Google Scholar 

  20. Narvekar, M., Fargose, P.: Daily weather forecasting using artificial neural network. Int. J. Comput. Appl. 121(22) (2015)

    Article  Google Scholar 

  21. Shastri, M.S., Gunge, A.K.: Neural network based weather prediction model towards ideal crop selection. Int. J. Eng. Comput. Sci. 5(9) (2016)

    Google Scholar 

  22. Saba, T., Rehman, A., AlGhamdi, J.S.: Weather forecasting based on hybrid neural model. Appl. Water Sci. 7(7), 3869–3874 (2017)

    Article  Google Scholar 

  23. Lee, J.H., Delbruck, T., Pfeiffer, M.: Training deep spiking neural networks using backpropagation. Front. Neurosci. 10, 508 (2016)

    Google Scholar 

  24. Rumelhart, D.E., McClelland, J.L.: Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Volume 1. Foundations (1986)

    Google Scholar 

  25. Günther, F., Fritsch, S.: neuralnet: training of neural networks. R J. 2(1), 30–38 (2010)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India

    Bhavya Alankar, Nowsheena Yousf & Shafqat Ul Ahsaan

Authors
  1. Bhavya Alankar
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  2. Nowsheena Yousf
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  3. Shafqat Ul Ahsaan
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Corresponding author

Correspondence to Shafqat Ul Ahsaan .

Editor information

Editors and Affiliations

  1. Siksha ‘O’ Anusandhan University, Bhubaneswar, India

    Srikanta Patnaik

  2. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    Andrew W. H. Ip

  3. Department of Business Systems and Analytics, La Salle University, Philadelphia, PA, USA

    Madjid Tavana

  4. Victoria Business School, School of Management, Victoria University of Wellington, Wellington, New Zealand

    Vipul Jain

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Alankar, B., Yousf, N., Ahsaan, S.U. (2020). Predictive Analytics for Weather Forecasting Using Back Propagation and Resilient Back Propagation Neural Networks. In: Patnaik, S., Ip, A., Tavana, M., Jain, V. (eds) New Paradigm in Decision Science and Management. Advances in Intelligent Systems and Computing, vol 1005. Springer, Singapore. https://doi.org/10.1007/978-981-13-9330-3_10

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