Intelligent Operation and Maintenance Method of Zone Area Based on Machine Learning Expert Model

Acquisition operations closed-loop management system as electricity information acquisition system output work unified export, established the acquisition operations standardization online control process, standardize the abnormal processing link, however with the complex business scenarios and work order processing timeliness requirements, homework redundancy, receive task source, lack of effective invalid business data filtering means, a large number of high mechanical, repetitive task consumes a lot of human resources, limit the operational efficiency and quality of further improve, need to improve acquisition operations closed loop automation analysis and intelligent auxiliary ability. Therefore, this paper puts forward a kind of intelligent operations method and device based on machine learning expert model of the area, first based on logical regression machine algorithm, learning the users behavior habits and daily work focus on index data, realize focus on index refining, electricity abnormal monitoring, equipment fault warning, and then according to the probability of the output of logical regression algorithm intelligent generate work order, finally usingRobotic Process Automation software in accordance with the rules to realize data acquisition, work order generation and processing of automation, improve the automation level. Effectively promoted the transformation of the management mode from extensive to refined, and the duration of closed-loop work order processing increased by 49.4%.