Meter reading data exception analysis method based on deep learning algorithm

Abstract

The invention discloses a meter reading data exception analysis method based on a deep learning algorithm, and relates to the field of power consumer meter reading exception judgment methods. In the past, a field detection method is mostly adopted for processing abnormal opinion complaints of the meter reading data, material resources and human resources are consumed, the efficiency is low, and the problems of single method, low accuracy and the like also exist for judging the determined abnormal user error electric quantity of the meter reading data. According to the method, a BP neural network subjected to deep learning training is adopted to establish a user meter reading data exception subordination judgment algorithm model and an optimal configuration strategy; quick and accurate judgment of work order user meter reading data abnormity affiliation is realized, and accurate estimation of error time and error electric quantity is realized by establishing a meter reading data abnormity user daily electricity consumption prediction model and an optimal configuration strategy. Therefore, the working efficiency of 95598 index analysis and quality control is improved, and an auxiliary decision-making effect is achieved.

Description

technical field [0001] The invention relates to the field of meter reading abnormality determination methods for power users, in particular to a method for analyzing abnormality of meter reading data based on a deep learning algorithm. Background technique [0002] Quickly and accurately handling user complaints about abnormal meter reading data is not only related to the economic interests of the power company, but also related to the service quality of the power company. Historically, on-site detection methods have been used to deal with complaints about abnormal meter reading data, that is, grid technicians go to the power consumption site to conduct investigations. There are also great human factors, which are not conducive to the management of the electric power industry. At the same time, there are also problems such as single method and low accuracy in determining the error power of users with abnormal meter reading data. Contents of the invention [0003] The tec...

AI Technical Summary

Problems solved by technology

Historically, on-site detection methods have been used to deal with complaints about abnormal meter reading data, that is, grid technicians go to the power consumption site to conduct investigations. There are also great human factors, which are not conducive to the management of the power industry

At the same time, there are also problems such as single method and low accuracy in determining the error power of users with abnormal meter reading data.

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