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Demand Forecasting in Smart Grids
Bell Labs Technical Journal, 2014Data analytics in smart grids can be leveraged to channel the data downpour from individual meters into knowledge valuable to electric power utilities and end-consumers. Short-term load forecasting (STLF) can address issues vital to a utility but it has traditionally been done mostly at system (city or country) level.
Piotr Mirowski +3 more
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, 2011 Companies operate in an increasingly challenging environment that requires them to continuously improve all areas of the business process. Demand forecasting is one area in manufacturing companies where we can hope to gain great advantages. Improvements in forecasting can result in cost savings throughout the supply chain, improve the reliability of ...
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Forecasting and Forecasts of Demand and Output
1984Forecasting is the process of using data about the past and present to predict the future. Some assumptions about the future are necessary as a basis for almost any type of decision. The assumptions may be based on a `hunch’ or on a systematic use of whatever data are relevant. The `hunch’ forecaster may produce a better prognostication than the formal
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Tourism Demand Forecasting: A Decomposed Deep Learning Approach
Journal of Travel Research, 2021Yishuo Zhang, Gang Li, Birgit Muskat
exaly
Tourism demand forecasting using tourist-generated online review data
Tourism Management, 2022Mingming Hu, Hengyun Li, Haiyan Song
exaly
An optimized model using LSTM network for demand forecasting
Computers and Industrial Engineering, 2020Hossein Abbasimehr, Mostafa Shabani
exaly