Short-Term Load Forecasting by Artificial Intelligent Technologies

In last few decades, short-term load forecasting (STLF) has been one of the most important research issues for achieving higher efficiency and reliability in power system operation, to facilitate the minimization of its operation cost by providing accurate input to day-ahead scheduling, contingency...

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Dettagli Bibliografici

Autori principali:	Wei-Chiang Hong (Ed.), Guo-Feng Fan (Ed.), Ming-Wei Li (Ed.)
Natura:	Online
Lingua:	inglese
Pubblicazione:	MDPI - Multidisciplinary Digital Publishing Institute 2021
Soggetti:	QA75.5-76.95 TK7885-7895 meta-heuristic algorithms artificial neural networks (ANNs) knowledge-based expert systems statistical forecasting models evolutionary algorithms short term load forecasting novel intelligent technologies support vector regression/support vector machines seasonal mechanism thema EDItEUR::U Computing and Information Technology::UY Computer science
Accesso online:	32122
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