Abstract
The Euclidean distance (ED), the mean absolute error (MAE), the mean absolute percentage error (MAPE) and the root of the mean quadratic error (RMQE) are used to evaluate the predictive capability of the models supported by each statistical method, asserting, according to the assessment, that the best predictions come from the ARIMA method. This paper presents a prediction study for two buildings located at the University of Mumbai in India, in order to determine a method that fits the forecasts of organization expenses.
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Viloria, A. et al. (2019). Analyzing and Predicting Power Consumption Profiles Using Big Data. In: Wang, G., Bhuiyan, M.Z.A., De Capitani di Vimercati, S., Ren, Y. (eds) Dependability in Sensor, Cloud, and Big Data Systems and Applications. DependSys 2019. Communications in Computer and Information Science, vol 1123. Springer, Singapore. https://doi.org/10.1007/978-981-15-1304-6_31
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