Hybrid Advanced Techniques for Forecasting in Energy Sector

• Päätekijä: Wei-Chiang Hong (Ed.) (auth)
• Aineistotyyppi: Elektroninen Kirjan osa
• Kieli: englanti
• Julkaistu: MDPI - Multidisciplinary Digital Publishing Institute 2018
• Aiheet: Computer science; hybrid models; autoregressive moving average with exogenous variable (ARMAX); energy forecasting; fuzzy group; quantile forecasting; evolutionary algorithms; quantum computing mechanism; cluster validity; support vector regression / support vector machines; artificial neural networks; principal component analysis; bayesian inference
• Linkit: DOAB: download the publication; DOAB: description of the publication

Accurate forecasting performance in the energy sector is a primary factor in the modern restructured power market, accomplished by any novel advanced hybrid techniques. Particularly in the Big Data era, forecasting models are always based on a complex function combination, and energy data are always...