Intelligent wastewater monitoring method and system based on complex network multivariate online regression

Abstract

The invention discloses an intelligent wastewater monitoring method based on complex network multivariate online regression, which comprises the following steps: collecting historical data including independent variables and dependent variables; performing normalization processing on the collected historical data to obtain a normalization model, and training the normalization model to obtain a trained normalization model; taking the independent variable as the input of the normalized model after training, carrying out the online learning of the normalized model after training, and updating thestate of the model in real time; performing reverse normalization processing on the output dependent variable to obtain a predicted dependent variable, and further regulating and controlling the wastewater treatment system. The complex network multivariate online regression method constructed by the invention solves the problem of poor generalization performance of deep learning on long and shortsequence regression, can be used for water quality parameter prediction, realizes intelligent water quality monitoring of a wastewater treatment system, and promotes efficient and stable operation ofthe wastewater treatment system.

Description

technical field [0001] The invention relates to the research field of waste water treatment and control, in particular to a waste water intelligent monitoring method and system based on complex network multivariate online regression. Background technique [0002] In the wastewater treatment process, there are a large number of parameters that are difficult to measure or cannot be measured online, and these parameters closely affect the control of effluent indicators. [0003] At present, the chemical oxygen demand (COD) and suspended solids (SS) of the effluent in the process of wastewater treatment mainly use traditional regression methods based on statistical methods such as principal component regression (PCR) and partial least squares regression (PLSR). , multiple linear regression (MLR), etc., backpropagation artificial neural network regression (BP-ANN) based on machine learning methods, support vector regression (SVR), etc., convolutional neural network regression (CN...

AI Technical Summary

Problems solved by technology

[0006] The main purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, and provide an intelligent monitoring method for wastewater based on complex network multivariate online regression, aiming at solving the problem that the generalization performance of deep learning for long and short sequence regression is not strong

Images