Abstract: A control method based on an adaptive neural network model for dissolved oxygen of an aeration system includes: obtaining related water quality monitoring data of a sewage treatment plant, and performing data preprocessing on the related water quality monitoring data; performing principal component analysis on the preprocessed related water quality monitoring data and a dissolved oxygen concentration of the aeration system through a principal component analysis method, and determining a water quality parameter with a highest rate of contribution to a principal component; taking the water quality parameter with the highest rate of contribution to the principal component, and predicting a dissolved oxygen concentration of the aeration system; and optimizing a dissolved oxygen predictive value obtained by means of the adaptive neural network model to obtain an optimal regulation value, and performing online regulation on a fuzzy control system of the adaptive neural network model.

Abstract: A control method based on an adaptive neural network model for dissolved oxygen of an aeration system includes: obtaining related water quality monitoring data of a sewage treatment plant, and performing data preprocessing on the related water quality monitoring data; performing principal component analysis on the preprocessed related water quality monitoring data and a dissolved oxygen concentration of the aeration system through a principal component analysis method, and determining a water quality parameter with a highest rate of contribution to a principal component; taking the water quality parameter with the highest rate of contribution to the principal component, and predicting a dissolved oxygen concentration of the aeration system; and optimizing a dissolved oxygen predictive value obtained by means of the adaptive neural network model to obtain an optimal regulation value, and performing online regulation on a fuzzy control system of the adaptive neural network model.

Abstract: The present disclosure discloses a method for removing TBBPA in water, a microbial strain and a microbial agent, wherein the microbial strain is a domesticated Burkholderia cepacia strain, which is named Y17 with a conservation number GDMCC No. 62153. The microbial agent and the method for removing TBBPA in water with the microbial agent are that Y17 strains are colonized on the surface and pore channels of biochar, TBBPA in water is used as a carbon source, air and dissolved oxygen are used as oxygen sources, biochar provides the strains a growth microenvironment for degrading TBBPA in water, the strains are subjected to aerobic growth in water, and bio-enhanced degradation of TBBPA in water is performed by continuously degradation reaction. The removal method and the microbial strain as well as the microbial agent are high in degradation efficiency, environmental-friendly and low in cost, and can meet requirements on large-range promotion and application.