Daily rainfall prediction using long short-term memory (LSTM) algorithm

Authors

  • B SUDARSAN PATRO Climate Research & Services, India Meteorological Department, Shivajinagar-411005, Pune, Maharashtra, India
  • PRASHANT P. BARTAKKE Department of Electronics & Telecommunication Engineering, COEP Technological University, Shivajinagar-411005, Pune, Maharashtra, India

DOI:

https://doi.org/10.54386/jam.v26i4.2745

Keywords:

Rainfall prediction, LSTM

References

Barrera-Animas, A.Y., Oyedele, L.O., Bilal, M., Akinosho, T.D., Delgado, J.M.D. and Akanbi, L.A., (2022). Rainfall prediction: A comparative analysis of modern machine learning algorithms for time-series forecasting. Mach. Learn. Appl., 7:100204.

Chen, C., Zhang, Q., Kashani, M.H., Jun, C., Bateni, S.M., Band, S.S., Dash, S.S. and Chau, K.W., (2022). Forecast of rainfall distribution based on fixed sliding window long short-term memory. Eng. Appl. Comput. Fluid Mech., 16(1):248-261.

Endalie, D., Haile, G., & Taye, W. (2022). Deep learning model for daily rainfall prediction: Case study of Jimma, Ethiopia. Water Supply, 22(3):3448-3461.

Frame, J.M., Kratzert, F., Klotz, D., Gauch, M., Shalev, G., Gilon, O., Qualls, L.M., Gupta, H.V. and Nearing, G.S., (2022). Deep learning rainfall–runoff predictions of extreme events. Hydrol. Earth Syst. Sci., 26(13):3377-3392.

Gauch, M., Kratzert, F., Klotz, D., Nearing, G., Lin, J. and Hochreiter, S., (2021). Rainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory network. Hydrol. Earth Syst. Sci., 25(4):2045-2062.

Gill, K. K., Bhatt, K., Kaur, B., and Sandhu, S. S. (2023). ARIMA approach for temperature and rainfall time series prediction in Punjab. J. Agrometeorol., 25(4): 571–576. https://doi.org/10.54386/jam.v25i4.2250

Poornima, S., and M. Pushpalatha. (2019). Prediction of rainfall using intensified LSTM based recurrent neural network with weighted linear units. Atmosphere 10.11 (2019): 668.

Ray, Mrinmoy, K. N. Singh, Soumen Pal, Amit Saha, Kanchan Sinha, and Rajeev Ranjan Kumar. (2023). Rainfall prediction using time-delay wavelet neural network (TDWNN) model for assessing agrometeorological risk. J. Agrometeorol., 25(1): 151–157. https://doi.org/10.54386/jam.v25i1.1895

Sherstinsky, A. (2020). Fundamentals of recurrent neural network (RNN) and long short-term memory (LSTM) network. Physica D, 404, 132306

Vaidya, V. B., Pandey, V., and Dhabale, S. (2023). Ancient science of weather forecasting in India with special reference to rainfall prediction. J. Agrometeorol., 25(4): 477–490. https://doi.org/10.54386/jam.v25i4.2422

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Published

01-12-2024

How to Cite

PATRO, B. S., & BARTAKKE, P. P. (2024). Daily rainfall prediction using long short-term memory (LSTM) algorithm. Journal of Agrometeorology, 26(4), 509–511. https://doi.org/10.54386/jam.v26i4.2745

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Short Communication

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