A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Study on Landslide Early Warning Based on Logistic Regression and Collaborative Filtering
In view of the shortcomings in the current research on the accuracy of landslide disaster early warning and the relationship between multiple landslides, this paper combines the collaborative filtering method and the logical regression training method to improve on the previous research on early warning only for a single landslide. The results show that the combination of the collaborative filtering method can use the similarity between landslides to predict, and the model training results have been significantly improved. The prediction of landslide disasters has a higher recall rate, which is of great significance to the prevention and control of landslide disasters.
Study on Landslide Early Warning Based on Logistic Regression and Collaborative Filtering
In view of the shortcomings in the current research on the accuracy of landslide disaster early warning and the relationship between multiple landslides, this paper combines the collaborative filtering method and the logical regression training method to improve on the previous research on early warning only for a single landslide. The results show that the combination of the collaborative filtering method can use the similarity between landslides to predict, and the model training results have been significantly improved. The prediction of landslide disasters has a higher recall rate, which is of great significance to the prevention and control of landslide disasters.
Study on Landslide Early Warning Based on Logistic Regression and Collaborative Filtering
Jiang, Xin (author) / Xinhua, E (author) / Zhao, Wenyi (author)
2023-01-01
861927 byte
Conference paper
Electronic Resource
English
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