Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast

• Andere auteurs: Gómez Vela, Francisco A. (Redacteur), García-Torres, Miguel (Redacteur), Divina, Federico (Redacteur)
• Formaat: Elektronisch Hoofdstuk
• Taal: Engels
• Gepubliceerd in: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Onderwerpen: 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
• Online toegang: DOAB: download the publication; DOAB: description of the publication

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...