Load Prediction of RBF Neural Network Considering Weather Factors

Autor:	Zhen Zhu Wei, Jian Dong Jiang, Ren Ran Wei, Hai Bo Yang
Rok vydání:	2013
Předmět:	Probabilistic neural network Artificial neural network Computer science Load forecasting Radial basis function General Medicine Data mining Weather factors computer.software_genre computer
Zdroj:	Applied Mechanics and Materials. :1103-1106
ISSN:	1662-7482
Popis:	In order to improve the precision of the short-term load prediction, a new method based on radial basis function (RBF) neural network is proposed. The weather data of samples includes the temperature, humidity, date, type, etc., and is quantified according the relevance to load, and then forecasting the power load using RBF neural network model in a region, Actual example shows that this method improves the convergence speed and prediction accuracy of load forecasting.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::f1c7d6099cda61376d278b7c9c9f0207 https://doi.org/10.4028/www.scientific.net/amm.397-400.1103 Zobrazit plný text záznamu