Titlebook: Data Analytics in Power Markets; Qixin Chen,Hongye Guo,Yi Wang Book 2021 Science Press 2021 Power markets.bidding strategy.machine learnin

僵局

書目名稱Data Analytics in Power Markets影響因子(影響力)




書目名稱Data Analytics in Power Markets影響因子(影響力)學(xué)科排名




書目名稱Data Analytics in Power Markets網(wǎng)絡(luò)公開度




書目名稱Data Analytics in Power Markets網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Data Analytics in Power Markets被引頻次




書目名稱Data Analytics in Power Markets被引頻次學(xué)科排名




書目名稱Data Analytics in Power Markets年度引用




書目名稱Data Analytics in Power Markets年度引用學(xué)科排名




書目名稱Data Analytics in Power Markets讀者反饋




書目名稱Data Analytics in Power Markets讀者反饋學(xué)科排名

性冷淡

Radiation

Ingratiate

Book 2021oaches. It begins with an overview of the power market data and analyzes on their characteristics and importance for market clearing. Then, the first part of the book discusses the essential problem of bus load forecasting from the perspective of market organizers. The related works include load unc

PAC

Moderate

Moderate

https://doi.org/10.1007/978-3-642-74748-9 obtained. On this basis, different quantile regression models are implemented to combine these point forecasts in order to form the final probabilistic forecasts. Case studies on a real-world dataset demonstrate the superiority of our proposed method.

Anthrp

https://doi.org/10.1007/978-3-030-38456-2 to detect local fluctuation. How the data cleaning influences the forecasting performance is also investigated. Case studies on the load data of Fujian Province, China are conducted to verify the effectiveness of the proposed method.

擁護

Notify

Load Data Cleaning and Forecasting to detect local fluctuation. How the data cleaning influences the forecasting performance is also investigated. Case studies on the load data of Fujian Province, China are conducted to verify the effectiveness of the proposed method.