Landslide Hazard Evaluation Based on SSA-BP
Pages 317 - 321
Abstract
Landslide has a wide distribution in our country, as a serious geological disaster threatening the life and property safety of our people, by evaluating the risk of landslide disasters, reasonable measures can be taken in advance to reduce the economic losses caused to the country, which has a high social value. In this paper, Zhenba County, Hanzhong City, Shaanxi Province, is taken as the study area, and on the basis of the collected geographic data, the data are processed using the GIS platform to analyse the distribution pattern of landslide disasters. Eight influence factors, namely, elevation, slope, slope direction, lithology, distance from river, vegetation coverage (NDVI), rainfall, and distance from road, were selected as the evaluation indexes of landslide disaster. The grey scale correlation method was used to evaluate the relationship between the influence factors and landslide hazard, and the information quantity method was chosen to evaluate each influence factor in the study area, and the landslide hazard evaluation was obtained by three algorithms, namely, the information quantity superposition method, the support vector machine, and the SSA-BP, which were used to process the information quantity and complete the evaluation of landslide hazards respectively. Finally, by analysing the results of the three hazard evaluation maps, it can be seen that the evaluation results of the SSA-BP algorithm have higher evaluation accuracy and reliability compared with the superposition method and the support vector machine, which can provide theoretical support and practical reference for the evaluation of landslide hazards in engineering applications.
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Index Terms
- Landslide Hazard Evaluation Based on SSA-BP
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Published In
June 2024
1206 pages
ISBN:9798400710247
DOI:10.1145/3690407
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Published: 24 October 2024
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CAIBDA 2024
CAIBDA 2024: 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms
June 21 - 23, 2024
Zhengzhou, China
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