Sewage treatment target parameter prediction method based on machine learning and process simulation

Abstract

The invention discloses a sewage treatment target parameter prediction method based on machine learning and process simulation, and relates to the technical field of sewage treatment. The sewage treatment target parameter prediction method based on the machine learning and the process simulation comprises the following steps of establishing and maintaining a process simulation model and a machinelearning model at the same time; integrating the machine learning and the process simulation; and predicting one or more target parameters of the sewage treatment. The method is different from the single machine learning and is also different from a single process simulation model, but ingeniously complements the simulation model and the machine learning model at the aspects of data construction and error verification to form a new intelligent model, so that the quality of the historical samples accumulated during the sewage treatment process is well guaranteed, the balance of positive and negative samples is guaranteed, meanwhile, the reasonability of the sample space distribution is enhanced, and the machine learning effect is enhanced.

Description

technical field [0001] The invention relates to the technical field of sewage treatment, in particular to a method for predicting target parameters of sewage treatment based on machine learning and process simulation. Background technique [0002] At present, the activated sludge method is a process commonly used in urban sewage treatment and industrial wastewater treatment. In the production process of sewage treatment using activated sludge method, it is often necessary to focus on monitoring some indicators, such as whether the water quality of the effluent is up to standard, whether the key control parameters of the process match the current influent water and environmental changes, due to the collection of these indicators There is a time lag in the assay, so it is a common requirement in the sewage treatment process to predict the index as the target parameter. However, the sewage treatment process itself is a nonlinear system with multiple time variations, high coupl...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the deficiencies of the prior art, the present invention provides a method for predicting target parameters of sewage treatment based on machine learning and process simulation, which solves the problem of poor practical application effect of the machine learning method for predicting target parameters of sewage treatment

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