电力系统自动化Issue(8)：67-71,5.DOI:10.7500/AEPS20130601001
基于云计算技术的电力大数据预处理属性约简方法
An Attribute Reducing Method for Electric Power Big Data Preprocessing Based on Cloud Computing Technology
摘要
Abstract
In face of the conventional attribute reduction incapability of grid data preprocessing for its big volume,diversified types and high speed in the forthcoming age of big data,a new method of electric power big data preprocessing via attribute reduction based on cloud computing technology is put forward.The characteristics of the relative positive region theory of the rough set is analyzed,and a parallel attribute reducing algorithm named MP_POSRS that can calculate the number of elements in the relative positive region is designed by taking good advantages of the MapReduce model in this method.Finally,the experiments including operations on the decision table of power grid fault diagnosis and real data of wind power are performed on a Hadoop platform,the results showing that the method is effective and feasible for dealing with power grid big data,and with good speedup and scalability required by electric power big data preprocessing via attribute reduction.关键词
电力大数据/MapReduce/粗糙集/属性约简Key words
electric power big data/MapReduce/rough set/attribute reduction引用本文复制引用
曲朝阳,陈帅,杨帆,朱莉..基于云计算技术的电力大数据预处理属性约简方法[J].电力系统自动化,2014,(8):67-71,5.基金项目
国家自然科学基金资助项目(51077010,51277023)。@@@@This work is supported by National Natural Science Foundation of China(No.51077010,No.51277023) （51077010,51277023）
