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The purpose of this paper is to present an on-line modeling and controlling scheme based on the dynamic recurrent neural network for wastewater treatment system.

A control strategy based on rule adaptive recurrent neural network (RARFNN) is proposed in this paper to control the dissolved oxygen (D_O) concentration and nitrate nitrogen (S_No) concentration. The structure of the RARFNN is self-organized by a rule adaptive algorithm, and the rule adaptive algorithm considers the overall information processing ability of neural network. Furthermore, a stability analysis method is given to prove the convergence of the proposed RARFNN.

By application in the control problem of wastewater treatment process (WWTP), results show that the proposed control method achieves better performance compared to other methods.

The proposed on-line modeling and controlling method uses the RARFNN to model and control the dynamic WWTP. The RARFNN can adjust its structure and parameters according to the changes of biochemical reactions and pollutant concentrations. And, the rule adaptive mechanism considers the overall information processing ability judgment of the neural network, which can ensure that the neural network contains the information of the biochemical reactions.

The application of servo steel struts enables the active control of the excavation-induced deformation in foundation pits. However, there is currently only one design axial force for each servo steel strut, which requires in-situ axial force adjustments based on the experience of site engineers. The purpose of this study is to develop a method for determining the design axial forces of servo steel struts at different excavation steps.

In this study, a hybrid method for determining the design axial forces of servo steel struts in different excavation steps was established based on the combination of the elastic foundation beam model and nonlinear optimisation.

The hybrid method is capable of providing a better set of design axial forces than the original design method. The lateral wall displacement and bending moment could be better controlled. Ordinary steel struts should be prevented from being set between servo steel struts to avoid axial force losses.

The axial forces of the servo steel struts at different excavation steps should be designed to achieve better deformation control effects. Moreover, a well-designed set of axial forces can also reduce the internal forces of the retaining structure.

The hybrid method enables the determination of the design axial forces of servo steel struts at different excavation steps, which can guide axial force adjustments in practical projects.