Bailong Li
Biographic Data
| ID | 9967134 |
|---|---|
| NAME | Bailong Li |
| GIVEN NAMES | Bailong |
| FAMILY NAME | Li |
| SIGNATURE | LI B |
| AFFILIATIONS | Jilin University |
| ORCID | 0000-0002-9094-0076 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 0 |
A Research on Susceptibility Mapping of Multiple Geological Hazards in Yanzi River Basin, China
Collapses, landslides, and debris flows are the main geological hazards faced by mankind, which bring heavy losses of life and property to people every year. The purpose of this paper is to establish a method for determining the optimal weighting scheme for multiple geological hazard susceptibility mapping. The information gain ratio (IGR) method was used to analyze the predictive ability of the conditioning factors. The support vector machine (S…
Exploring Complementary Models Consisting of Machine Learning Algorithms for Landslide Susceptibility Mapping
Landslides frequently occur because of natural or human factors. Landslides cause huge losses to the economy as well as human beings every year around the globe. Landslide susceptibility prediction (LSP) plays a key role in the prevention of landslides and has been under investigation for years. Although new machine learning algorithms have achieved excellent performance in terms of prediction accuracy, a sufficient quantity of training samples i…
No prominent works on this page.
A Research on Susceptibility Mapping of Multiple Geological Hazards in Yanzi River Basin, China
Collapses, landslides, and debris flows are the main geological hazards faced by mankind, which bring heavy losses of life and property to people every year. The purpose of this paper is to establish a method for determining the optimal weighting scheme for multiple geological hazard susceptibility mapping. The information gain ratio (IGR) method was used to analyze the predictive ability of the conditioning factors. The support vector machine (S…
Exploring Complementary Models Consisting of Machine Learning Algorithms for Landslide Susceptibility Mapping
Landslides frequently occur because of natural or human factors. Landslides cause huge losses to the economy as well as human beings every year around the globe. Landslide susceptibility prediction (LSP) plays a key role in the prevention of landslides and has been under investigation for years. Although new machine learning algorithms have achieved excellent performance in terms of prediction accuracy, a sufficient quantity of training samples i…
Computer Science (2 works) · Data mining (2 works) · Engineering (2 works) · Geology (2 works) · Geotechnical engineering (2 works) · Landslide (2 works) · Landslides and related hazards (2 works) · Algorithm (1 work) · Analytic hierarchy process (1 work) · Artificial Intelligence (1 work)