Urban sewage treatment process data cleaning method based on dynamic interpolation

Abstract

The invention discloses a dynamic interpolation-based urban sewage treatment process data cleaning method, belongs to the field of sewage treatment, and aims to solve the problem of poor data quality caused by mixing of outliers and continuous repetitive values in urban sewage treatment process data. According to the dynamic interpolation method, data segments are segmented through a sliding window, abnormal factor coefficients of the segmented data segments are calculated, abnormal conditions of the data segments are judged, outliers and continuous abnormal values in the abnormal data segments are removed, missing data are compensated by adopting a random forest regression model, and the quality of the data in the urban sewage treatment process is improved. Experimental results show that the method improves the precision of data compensation, guarantees the data quality of a database in the urban sewage treatment industry, and improves the credibility of the research of a sewage treatment plant.

Description

technical field [0001] Based on the analysis of the operation data of the urban sewage treatment process, the present invention segments the data through a sliding window, calculates the abnormal factor coefficient in each segment of data, judges the abnormality of the data segment, removes the abnormal value of the abnormal data segment, and uses the random forest The regression model predicts interpolation, and realizes the cleaning of urban sewage treatment process data by means of dynamic interpolation. This urban sewage treatment process data cleaning method based on dynamic interpolation can clean the mixed data of outliers and continuous repeated values ​​contained in the urban sewage treatment process data in the actual process, and improve the credibility of the urban sewage treatment process data. It belongs to the field of sewage treatment. Background technique [0002] In the field of urban sewage treatment industry, due to the diversity of data sources, the com...

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Problems solved by technology

[0005] The present invention obtains a data cleaning method of urban sewage treatment process based on dynamic interpolation. The method divides the data segment through a sliding window, calculates the abnormal factor coefficient of the segmented data segment, and determines the abnormal situation of the data segment; outliers and continuous repeated values; the random forest regression model is used to compensate for missing data to obtain high-quality urban sewage treatment process data, which solves the problem of unsatisfactory treatment effect of outliers and continuous repeated values ​​in urban sewage treatment process data , which improves the data quality of urban sewage treatment process data and has better data accuracy

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