Power Load Forecasting Based on Parallel Shared Mining Algorithm
ZHAO Wenshuo
XIE Ping
WANG Ying
LI Yan
LIAO Yiming
Abstract：There are many factors that affect the power load ,and data for electric power load forecasting is also more and more .Traditional forecast methods can’t effectively establish power load forecasting model through mining large data . This paper puts forward a new method to establish a power load forecasting model ,combining the parallel shared data mining technology and analysising the parallel shared decision tree based on HADOOP algorithm(PSDT ) and the SLIQ algorithm . The experimental results show that ,using this method to establish power load forecasting model has better practicability , and has good scalability .
Keywords：data miningload forecastingHadoopparallel shared decision tree
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 178-182 )