Which algorithm in Forecast should the data scientists use to meet these requirements?
Autoregressive Integrated Moving Average (AIRMA)
Exponential Smoothing (ETS)
Convolutional Neural Network – Quantile Regression (CNN-QR)
Prophet
Explanations:
Amazon Forecast does not offer Autoregressive Integrated Moving Average (ARIMA) as an algorithm option. ARIMA is a classic statistical model for time series forecasting but does not natively support multiple related time series and external features like weather or public holidays.
Exponential Smoothing (ETS) is available in Amazon Forecast, but it is less suitable for complex data with multiple related time series and additional features like weather. ETS primarily models seasonality and trend but lacks support for covariates.
Convolutional Neural Network – Quantile Regression (CNN-QR) is available in Amazon Forecast and is suitable for time series data with covariates, including weather and holidays. It also supports probabilistic forecasting, which is useful for energy consumption forecasting.
Prophet is not an option available in Amazon Forecast. Prophet, developed by Facebook, is primarily used in separate forecasting environments and is limited in its ability to incorporate complex covariates and external data sources.
I systematize that the answer is:
Convolutional Neural Network – Quantile Regression (CNN-QR)
I outline that the answer is:
Convolutional Neural Network – Quantile Regression (CNN-QR)