How would you approach a time series analysis for predicting energy consumption patterns in a city with rapidly changing weather conditions?
- Implement machine learning algorithms without considering weather data
- Rely solely on historical energy consumption data for accurate predictions
- Use a combination of meteorological data and time series models such as ARIMA or SARIMA
- Use simple moving averages to smooth out fluctuations
In this scenario, incorporating meteorological data along with time series models like ARIMA or SARIMA would be essential. The weather conditions can significantly impact energy consumption, and using only historical data might not capture the variations due to changing weather. Machine learning algorithms may be used in conjunction, but it's crucial to consider weather factors.
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