Automatic division method for catchment area of urban drainage pipe network

A drainage pipe network and automatic division technology, applied in the direction of neural learning methods, biological neural network models, instruments, etc., can solve the problem of low efficiency of catchment area division, achieve division accuracy improvement, improve modeling efficiency, and accelerate modeling The effect of the process
CN112712033AActive Publication Date: 2021-04-27HARBIN INST OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HARBIN INST OF TECH
Publication Date
2021-04-27

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Abstract

The invention discloses an automatic division method for a catchment area of an urban drainage pipe network, solves the problem of low division efficiency of an existing catchment area, and belongs to the field of cross application of environmental engineering, visible light remote sensing image semantic segmentation and computer vision. The method comprises the following steps: S1, acquiring a remote sensing image of an urban target area, and constructing a training data set; S2, utilizing a convolutional neural network coupling variant residual network to construct a road network extraction convolutional neural network model, and using a variant residual network as a coding structure of the convolutional neural network; S3, training a road network extraction convolutional neural network model by using the training data set, and determining parameters of the road network extraction convolutional neural network model; S4, inputting the remote sensing image of the city area to be divided into a road network extraction convolutional neural network model, and extracting road network information; and S5, dividing the extracted road network information into water catchment area, and further dividing sub-water catchment areas by using an inverse distance weighted Thiessen polygon method in combination with prior information of rainwater well point distribution.
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Description

technical field

[0001] The invention relates to a method for automatically dividing urban drainage pipe network catchment areas based on a convolutional neural network coupling variant residual learning unit, and belongs to the cross-application fields of environmental engineering, visible light remote sensing image semantic segmentation, and computer vision. Background technique

[0002] The establishment process of the urban drainage network model mainly includes the division of catchment area, the input of pipe section parameters, the parameter setting of key wading facilities, and the calibration of sensitivity parameters. Among them, the division of catchment areas is the basis for the construction of the entire drainage network model, and the accuracy of the division results directly affects the calculation accuracy of urban rainwater infiltration, evaporation and runoff processes.

[0003] In the process of traditional urban drainage network modeling, the division of ...

Claims

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