微型电脑应用2023，Vol.39Issue(12)：58-61,84,5.
基于数据挖掘和LSSVM的电量大数据多维感知方法
Multidimensional Perception Method for Power Big Data Based on Data Mining and LSSVM
摘要
Abstract
In order to solve the problem of poor perception performance of the existing multidimensional perception methods of power big data,the optimal design of perception methods is realized by data mining technology and LSSVM algorithm.The multidimensional electricity data model is constructed by data mining technology.Through three steps of filling in missing data,correcting wrong data and data standardization,the characteristics of electricity big data are extracted from three aspects of trend,variability and load.The multidimensional electricity load variation is predicted by LSSVM algorithm,and the multidi-mensional perception of electricity big data is carried out.The experimental results show that the fitting error of this method is reduced by 8.4 kW,the sensitivity index is increased by 0.388,and the multidimensional perception performance of electricity big data is better.关键词
数据挖掘技术/LSSVM/电量大数据/多维感知Key words
data mining technology/LSSVM/electricity big data/multidimensional perception分类
信息技术与安全科学引用本文复制引用
岳宝强,杨波,李彪,曲小康,魏飞..基于数据挖掘和LSSVM的电量大数据多维感知方法[J].微型电脑应用,2023,39(12):58-61,84,5.基金项目
国网临沂供电公司2021年研究开发项目(5206002000VM) （5206002000VM）
