Mountain torrent disaster zoning method based on machine learning

A machine learning and mountain torrent technology, applied in the fields of instruments, computer parts, data processing applications, etc., can solve the problem of less attention to the zoning research of mountain torrent disasters

Active Publication Date: 2022-03-15
HOHAI UNIV
View PDF12 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in recent years, the research on mountain torrent disasters has mostly focused on risk a

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Mountain torrent disaster zoning method based on machine learning
  • Mountain torrent disaster zoning method based on machine learning
  • Mountain torrent disaster zoning method based on machine learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] A kind of flash flood disaster zoning method based on machine learning described in this embodiment, the flowchart is as follows figure 1 shown, including the following steps:

[0034] (1) Preprocess the impact factors of mountain torrent disasters, and extract various short-term heavy rainfall indicators and underlying surface data indicators:

[0035] Due to the problems of outliers and missing data in the original rainfall data, it is necessary to preprocess the original rainfall data before use, remove the outliers, make up for the missing data by interpolation, and finally obtain various short-term heavy rainfall indicators. The underlying surface data are resampled to obtain underlying surface data indicators with the same spatial resolution. Construct an index system that affects mountain torrent disasters, including short-term heavy rainfall factors, underlying surface data indicators, and small watershed attributes, and use these data as input factors that are...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a mountain torrent disaster zoning method based on machine learning. The mountain torrent disaster zoning method comprises the following steps: (1) extracting various short-time heavy rainfall indexes and underlying surface data indexes; (2) screening key factors of mountain torrent disasters from the short-time heavy rainfall index and the underlying surface data index; (3) constructing a self-organizing mapping neural network model (SOM) to perform primary spatial clustering on the mountain torrent disasters, and then performing secondary clustering; (4) comprehensively evaluating the secondary clustering result of the mountain torrent disasters by using the external indexes and the internal indexes, and determining an optimal clustering scheme of the mountain torrent disasters; and (5) calculating the standard deviation rate of the area of the zoning pattern spots, merging and processing the tiny patches, and obtaining a final mountain torrent disaster zoning result. According to the method, key factors related to mountain torrent disasters are selected through a random forest model, then two-stage hybrid clustering is carried out by utilizing SOM, and mountain torrent disaster space division is realized by combining various machine learning methods.

Description

technical field [0001] The invention relates to the field of mountain torrent disaster prevention and control, in particular to a method for zoning mountain torrent disasters based on machine learning. Background technique [0002] Mountain torrents are surface runoff that rises and falls rapidly in small watersheds in hilly areas due to short-duration heavy rainfall. Mountain torrents are one of the deadliest natural disasters in the world. They are sudden, concealed, destructive, and costly Serious and other characteristics, often causing casualties of residents, destroying building facilities, changing the shape of rivers and destroying the natural environment. With the intensification of extreme climate events and human activities, the problem of mountain torrent disasters has gradually attracted widespread attention and great attention from all over the world. The development of mountain torrent disaster zoning can effectively reflect the spatial differentiation patter...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06Q10/06G06Q50/26G06K9/62
CPCG06Q10/0635G06Q10/06393G06Q50/26G06F18/23G06F18/24323Y02A10/40
Inventor 陈跃红张若婧张晓祥
Owner HOHAI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap