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A High Precision Calibration Method for SWMM Model Parameters

A model parameter, high-precision technology, applied in computational models, biological models, neural learning methods, etc., can solve the problem that the SWMM parameter model is difficult to obtain accurately

Active Publication Date: 2021-07-27
CHINA INST OF WATER RESOURCES & HYDROPOWER RES
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Aiming at the above-mentioned deficiencies in the prior art, a high-precision calibration method of SWMM model parameters provided by the present invention solves the problem that the SWMM parameter model is difficult to obtain accurately

Method used

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  • A High Precision Calibration Method for SWMM Model Parameters
  • A High Precision Calibration Method for SWMM Model Parameters
  • A High Precision Calibration Method for SWMM Model Parameters

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Embodiment Construction

[0025] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0026] Such as figure 1 Shown, a kind of high-precision calibrating method of SWMM model parameter is characterized in that, comprises the following steps:

[0027] S1. Determine the uncertain parameters of the SWMM model that needs to be calibrated according to the actual situation; the uncertain parameters include the slow flow width coefficient Width in the confluence area, the Manning coefficient N-Imperv in the impervi...

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Abstract

The invention discloses a high-precision calibration method for SWMM model parameters. The present invention combines the artificial neural network model and the particle swarm optimization algorithm to calibrate the parameters of the SWMM model, and the present invention contributes to the scientific, accurate and efficient calibration of the model and avoids unnecessary waste of manpower, material resources and time.

Description

technical field [0001] The invention relates to the technical field of urban rain and flood process simulation, in particular to a high-precision calibration method for SWMM model parameters. Background technique [0002] With the acceleration of urbanization, the problem of urban waterlogging has become increasingly prominent. Accurate analysis of waterlogging characteristics is the key to urban flood control and drainage. At present, for urban waterlogging research, mathematical models are generally used to simulate and predict urban rain and flood processes. SWMM (Stormwater Management Model) is jointly developed by the U.S. Environmental Protection Agency and the Water Resources Center. It can simulate the runoff process in urban areas and simulate the water volume in sub-basins and pipelines at different times. As open source software, the SWMM mathematical model can be used with ArcGIS and other software are used in combination to improve modeling efficiency, so they ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/27G06F30/28G06N3/08G06N3/00G06F113/08
CPCG06N3/006G06N3/08
Inventor 陈文学何胜男穆祥鹏崔巍陈兴茹
Owner CHINA INST OF WATER RESOURCES & HYDROPOWER RES