Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast

The use of data collectors in energy systems is growing more and more. For example, smart sensors are now widely used in energy production and energy consumption systems. This implies that huge amounts of data are generated and need to be analyzed in order to extract useful insights from them. Such...

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Muut tekijät:	Gómez Vela, Francisco A. (Toimittaja), García-Torres, Miguel (Toimittaja), Divina, Federico (Toimittaja)
Aineistotyyppi:	Kirjan osa
Julkaistu:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Aiheet:	Research & information: general Technology: general issues deep learning energy demand temporal convolutional network time series forecasting time series forecasting exponential smoothing electricity demand residential building energy efficiency clustering decision tree time-series forecasting evolutionary computation neuroevolution photovoltaic power plant short-term forecasting data processing data filtration k-nearest neighbors regression autoregression n/a
Linkit:	Get Fullteks DOAB: description of the publication
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Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast

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