Abstract
Rainfall is an important hydro-climatic variable on which crop productivity, aridness etc. depend. Different time series analysis techniques, e.g. ARIMA, HWES etc. are typically used to predict rainfall. In this paper, authors applied different neural network techniques (ANN) for studying the rainfall time series in Burdwan district of West Bengal, India, by using past 15 years’ data. Then, efficiency of different ANN schemes to predict the rainfall was compared and best scheme was selected. All the calculation works were done using ANN model in MATLAB R2013a.
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Mishra, S.K., Sharma, N. (2018). Rainfall Forecasting Using Backpropagation Neural Network. In: Panda, B., Sharma, S., Batra, U. (eds) Innovations in Computational Intelligence . Studies in Computational Intelligence, vol 713. Springer, Singapore. https://doi.org/10.1007/978-981-10-4555-4_19
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DOI: https://doi.org/10.1007/978-981-10-4555-4_19
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