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What is Drought Prediction Using LSTM Models about?

This document summarizes a research paper that uses a Long Short-Term Memory (LSTM) recurrent neural network to predict drought indices at varying timescales based on the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). It compares the 1, 6, and 12-month predictions of an Autoregressive Integrated Moving Average (ARIMA) statistical model to the LSTM model using multivariate inputs to improve performance. Drought prediction is challenging but important fo

Author

María Angélica Andrade

Language

EN