Abstract
The demand for electricity has been continuously increasing over the years. To understand the future consumption, a good predictive model is entailed. The ARIMA models have been extensively used for time series prediction showing encouraging results. In this paper, an attempt is made on forecasting the electricity consumption using the ARIMA model. Using the mean absolute percentage error (MAPE) to measure forecast accuracy, the model was able to forecast with an error of 6.63%. Results shows that the ARIMA model has a potential to compete with existing techniques for electricity consumption forecast.
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Jain, P.K., Quamer, W., Pamula, R. (2018). Electricity Consumption Forecasting Using Time Series Analysis. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 906. Springer, Singapore. https://doi.org/10.1007/978-981-13-1813-9_33
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