沈阳工业大学学报2024，Vol.46Issue(3)：255-262,8.DOI:10.7688/j.issn.1000-1646.2024.03.03
基于IWOA-ELM-AE的电力资产信息管理系统异常数据检测方法
Abnormal data detection method based on IWOA-ELM-AE for power asset information management system
摘要
Abstract
Aiming at the problem that the current power asset information management system is difficult to detect abnormal data accurately and independently,a method based on IWOA-ELM-AE for detecting abnormal data in the power asset information management system was proposed.The analysis for possible anomaly types under the framework of the management system was performed,the improved whale optimization algorithm(IWOA)was used to optimize the ELM-AE,and the corresponding abnormal data optimization detection model for power information system was established.The as-proposed model was applied to the detection of abnormal data of power asset information,and the performance evaluation index system was established to measure its effect.The results show that the test performance evaluation results of as-proposed method has remarkable advantages over the traditional model,and can detect the abnormal data in the power asset information more accurately.关键词
信息管理系统/电力资产/异常数据检测/极限学习机/自编码器/鲸鱼优化算法/检测性能/评估指标Key words
information management system/power asset/abnormal data detection/extreme learning machine/auto-encoder/whale optimization algorithm/test performance/evaluation index分类
动力与电气工程引用本文复制引用
李凯,靳书栋,刘宏志,王艳梅,杨晓营..基于IWOA-ELM-AE的电力资产信息管理系统异常数据检测方法[J].沈阳工业大学学报,2024,46(3):255-262,8.基金项目
山东省科技计划项目(S2021RCDT2B0826). （S2021RCDT2B0826）
