Hybrid EMD-RF Model for Predicting Annual Rainfall in Kerala, India
نویسندگان
چکیده
Rainfall forecasting is critical for the economy, but it has proven difficult due to uncertainties, complexities, and interdependencies that exist in climatic systems. An efficient rainfall model will be beneficial implementing suitable measures against natural disasters such as floods landslides. In this paper, a novel hybrid of empirical mode decomposition (EMD) random forest (RF) was developed enhance accuracy annual prediction. The EMD technique utilized decompose signal into six intrinsic functions (IMFs) extract underlying patterns, while RF algorithm employed make predictions based on IMFs. RF–IMF trained tested using dataset Kerala from 1871 2020, its performance compared traditional models regression autoregressive moving average (ARMA) model. Mean absolute error (MAE), mean percentage (MAPE), squared (MSE), root (RMSE), coefficient determination or R-squared (R2) were used compare performances these three models. Model evaluation metrics show outperformed both ARMA
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2023
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app13074572