Landslide grading system and method based on convolutional support vector neural network

Abstract

The invention provides a landslide grading system and method based on a convolutional support vector neural network, and belongs to the field of roadbed engineering. The landslide grading system basedon a convolutional support vector neural network comprises an image storage module used for storing collected images, an image acquisition module used for acquiring image data, and an image processing module used for carrying out landslide classification and discrimination on images. The image processing module comprises an image discrimination unit used for discriminating whether landslide exists in the images or not and an image classification unit used for carrying out landslide classification on the images. The landslide grading is judged by collecting the images and analyzing the images,so that the manpower is saved, the efficiency is high, and no safety risk exists.

Description

technical field [0001] The invention relates to the field of roadbed engineering, and mainly relates to a landslide classification system and method based on a convolutional support vector neural network. Background technique [0002] In the past, due to low grade, poor alignment, low roadbed, and low excavation, slope stability had no significant impact on safety, and people did not pay enough attention to slope stability. However, with the development of national economic construction , the traffic industry is changing with each passing day, the level is getting higher and higher, and high filling and deep excavation are inevitable. The construction of high-grade highways under complex terrain conditions is increasing, and there have been many large-scale landslides at home and abroad. Landslides not only affect driving safety, Even burying, interrupting the traffic, forcing the abandonment of the completed use, resulting in immeasurable economic losses, the research on th...

AI Technical Summary

Problems solved by technology

[0002] In the past, due to low grade, poor alignment, low roadbed, and low excavation, slope stability had no significant impact on safety, and people did not pay enough attention to slope stability. However, with the development of national economic construction , the traffic industry is changing with each passing day, the level is getting higher and higher, and high filling and deep excavation are inevitable. The construction of high-grade highways under complex terrain conditions is increasing, and there have been many large-scale landslides at home and abroad. Landslides not only affect driving safety, Even burying, interrupting traffic, forcing the abandonment of the completed use, causing immeasurable economic losses, it is imminent to study the causes and prevention of landslides

[0003] In the prior art, the usual landslide classification requires manual measurement of landslide soil volume on site, that is, landslide classification; existing methods usually consume resources such as manpower, equipment and time, and will bring safety risks to engineering personnel. Manual on-site landslide classification is of limited use

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