An optimization method for design parameters of water environment governance projects based on deep learning

Abstract

The invention discloses a method for optimizing design parameters of a water environment treatment project based on deep learning, comprising: constructing a conceptual model of the water environment treatment area based on the basic information of the water environment treatment area; The numerical model of the area is used to correct the numerical model of the water environment treatment area; the numerical model of the corrected water environment treatment area is run to generate an alternative model training sample; based on the alternative model training sample, deep learning is used to train the alternative model; The trained surrogate model is used for multi-objective optimization calculation of design parameters of water environment treatment projects; this method solves the problem that the optimal design parameter set cannot be obtained in the process of traditional design parameter formulation; It is fully considered and incorporated into the final design parameter optimization calculation process; it can carry out multi-objective optimization analysis for the design of water environment treatment projects.

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 of water environment treatment projects is an important link in water environment treatment projects and the basis for the implementation of subsequent projects. Scientific optimization of design parameters is an important guarantee for the implementation quality of water environment treatment projects. [0003] At present, the traditional method for formulating design parameters of water environment treatment projects is: firstly observe and collect basic water environment parameters (hydrology, meteorology, hydraulic conditions and water quality conditions, etc.) of the treatment area, and then perform statistical and trend analysis on the obtained data information , and further use...

AI Technical Summary

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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