Water environment treatment project design parameter optimization method based on deep learning

Abstract

The invention discloses a water environment treatment project design parameter optimization method based on deep learning. The method comprises the steps of constructing a conceptual model of a waterenvironment treatment area based on basic information of the water environment treatment area; constructing a numerical model of the water environment treatment area based on the conceptual model of the water environment treatment area, and correcting the numerical model of the water environment treatment area; running the corrected numerical model of the water environment treatment area to generate a substitution model training sample; training the substitution model by using deep learning based on the substitution model training sample; performing multi-objective optimization calculation ofwater environment treatment project design parameters based on the trained substitution model. According to the method, the problem that an optimal design parameter set cannot be obtained in a traditional design parameter making process is solved; behaviors of all subsystems in the water environment system can be fully considered and brought into the final design parameter optimization calculationprocess; and multi-objective optimization analysis can be carried out on the design work of a water environment treatment project.

Description

technical field [0001] The invention relates to the field of water environment treatment project design, in particular to a method for optimizing design parameters of water environment treatment projects based on deep learning. Background technique [0002] The formulation of design parameters for water environment treatment projects is an important link in water environment treatment projects and the basis for the implementation of subsequent projects. The scientific optimization of design parameters is an important guarantee for the implementation quality of water environment treatment projects. [0003] At present, the traditional method of formulating design parameters for water environment governance projects is: first observe and collect basic water environment parameters (hydrology, meteorology, hydraulic conditions, water quality conditions, etc.) in the governance area, and then conduct statistics and trend analysis on the obtained data information , and further us...

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Problems solved by technology

[0008] The present invention provides a method for optimizing design parameters of water environment treatment projects based on deep learning. This method effectively solves the problem that the optimal design parameter set cannot be obtained in the process of formulating traditional design parameters; at the same time, the water environment treatment project design proposed by the present invention In the parameter optimization method, the water environment numerical model is introduced in the analysis process, which can fully consider the behavior of each subsystem in the water environment system and incorporate it into the final design parameter optimization calculation process; and the present invention can realize project design and cost The two-way feedback between controls can carry out multi-objective optimization analysis on the design work of water environment treatment projects

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