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To compare their forecasting accuracy, three simple regression models (Linear, elastic net and Poisson regression), three time-series models (ARIMA, SARIMA and SARIMAX), three machine-learning models (Support vector machines, random forest, extreme gradient boosting), two deep-learning models (artificial neural networks and long-short term memory) and five specialized hybrid models combining machine learning, deep learning and time-series models were trained and then tested on data spanning from 2001 to 2021

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Christensen K

doi: 10.1016/S0168-8278(98)80285-7