Intelligent Preprocessing Method of Sewage Measurement Data

Abstract

The invention discloses an intelligent preprocessing method for sewage measurement data. The method includes the following steps: 1) preprocessing the time series-based data used for sewage water quality prediction or control; 2) determining the intelligent model, the input feature quantity in the preprocessing data, and the target feature quantity in the preprocessing data ; 3) Group the input feature quantities in the preprocessing data according to the positions of the actual measurement points; 4) Each group of input feature quantities is traversed as a reference to the previous group of input feature quantities, and the traversal unit is one sampling period, and output the combined 5) Utilize the data of the predetermined ratio after combination to carry out intelligent model training; 6) Utilize the remaining data after combination to calculate the mean square error value (MSE) of the smart model; 7) Update the time interval of each group of input feature quantities; 8) If the time interval of each group is less than or equal to the time of the whole sewage process, then return to step 4); 9) output the time interval with the smallest mean square error value in the traversal process, that is, obtain the time difference between each input feature quantity; 10) Recombine the data according to the time interval between each input feature quantity for intelligent model training.

Description

Technical field [0001] The invention belongs to the field of sewage data processing, and more particularly to a method of pretreatment of sewage measurement data when modeling using artificial intelligence technology. Background technique [0002] In my country, most urban sewage treatment plants were treated with active sludge. The sewage treatment process of the active sludge method is a strong coupled multi-input multi-output dynamic system, with a large lag, nonlinear, time-beam, and uncertainties, which brought difficult to modeling. [0003] Traditionally, people can model the actual system using the obtained extensive data knowledge, and widely used in the fields of various controls. However, for complex continuous, time-change, large lags and nonlinear sewage control systems, mathematical modeling methods are severely challenged. In recent years, with the development of artificial intelligence, it can be used to establish a black box mechanism model for sewage measurement...

AI Technical Summary

Problems solved by technology

However, since the measurement of sewage data is based on the same moment, and the sewage treatment system itself has a time lag, it is difficult to analyze the time series of sewage measurement characteristics in the process of intelligent modeling

Images