Article

Conventional time series, machine and deep learning approaches for rainfall forecasting in a bimodal climate in Embu County, Kenya: A comparative study of SARIMA, ANN, LSTM, CNN and hybrid models

2026-05-26

Abstract excerpt

<title>Abstract</title> <p>Accurate rainfall forecasting is critical for agricultural planning, water resource management, and climate risk reduction in regions characterized by strong seasonal variability and nonlinear climatic behaviour. This study evaluates the predictive performance of statistical, machine learning, and hybrid deep learning models for monthly rainfall forecasting in Embu County, Kenya, using...

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Literature Corpus work: aa807d4b-1e30-5e4e-b376-c4bb3824819d
DOI: 10.21203/rs.3.rs-9725114/v1

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Conventional time series, machine and deep learning approaches for rainfall forecasting in a bimodal climate in Embu County, Kenya: A comparative study of SARIMA, ANN, LSTM, CNN and hybrid modelsDOI 10.21203/rs.3.rs-9725114/v1Read

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