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- W4313443760 abstract "Currently, the industrial energy demand forecasting scenario in the state of Goa is in the nascent stages of development. The pharmaceutical industry contributes to 35–38% of the energy demand of the state, and therefore, forecasting pharmaceutical energy demand holds the key to industrial energy demand forecasting of the state. The electricity demand of a major pharmaceutical industry in the state, for the period from 2018 to 2020, is considered for forecasting. The key features of this demand dataset that complicate the forecasting process are a continuously shifting statistic, calendar effects, strong volatility and so on. The energy consumption data of the manufacturing plant under consideration is visualized as a time series data consisting of the two major components, i.e., the deterministic and stochastic. The deterministic and stochastic components are arrived at using a multiplicative decomposition technique. Within the deterministic component, special attention is placed on the weekly effect as it was ignored in the research till date. To address the forecasting accuracy, MAPE, MAE and RMSE are calculated." @default.
- W4313443760 created "2023-01-06" @default.
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- W4313443760 date "2023-01-01" @default.
- W4313443760 modified "2023-10-16" @default.
- W4313443760 title "Isolating Stochastic Component of Energy Demand of Pharmaceutical Industry" @default.
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- W4313443760 doi "https://doi.org/10.1007/978-981-19-6945-4_45" @default.
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