Luis F Robledo
Biographic Data
| ID | 7873675 |
|---|---|
| NAME | Luis F Robledo |
| GIVEN NAMES | Luis F |
| FAMILY NAME | Robledo |
| SIGNATURE | ROBLEDO L F |
| AFFILIATIONS | Universidad Andres Bello |
| ORCID | 0000-0003-0700-5835 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
On disasters evacuation modeling: From disruptive to slow-response decisions
Decision-making evacuation modeling for natural hazards has always been complex due to the uncertainty of variables affecting it. One of the most relevant existing assumptions for this kind of simulation is the use of sigmoid distributions (e.g., Rayleigh) to represent the evacuation times. We found some disadvantages in using this type of probability distribution for slow-response disasters (i.e., geological hazards applications), where there ma…
A Novel Hybrid Method for Landslide Susceptibility Mapping-Based GeoDetector and Machine Learning Cluster: A Case of Xiaojin County, China
Landslide susceptibility mapping (LSM) could be an effective way to prevent landslide hazards and mitigate losses. The choice of conditional factors is crucial to the results of LSM, and the selection of models also plays an important role. In this study, a hybrid method including GeoDetector and machine learning cluster was developed to provide a new perspective on how to address these two issues. We defined redundant factors by quantitatively a…
Determinant Factors in Personal Decision-Making to Adopt Covid-19 Prevention Measures in Chile
The pandemic has challenged countries to develop stringent measures to reduce infections and keep the population healthy. However, the greatest challenge is understanding the process of adopting self-care measures by individuals in different countries. In this research, we sought to understand the behavior of individuals who take self-protective action. We selected the risk homeostasis approach to identify relevant variables associated with the r…
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A Novel Hybrid Method for Landslide Susceptibility Mapping-Based GeoDetector and Machine Learning Cluster: A Case of Xiaojin County, China
Landslide susceptibility mapping (LSM) could be an effective way to prevent landslide hazards and mitigate losses. The choice of conditional factors is crucial to the results of LSM, and the selection of models also plays an important role. In this study, a hybrid method including GeoDetector and machine learning cluster was developed to provide a new perspective on how to address these two issues. We defined redundant factors by quantitatively a…
Determinant Factors in Personal Decision-Making to Adopt Covid-19 Prevention Measures in Chile
The pandemic has challenged countries to develop stringent measures to reduce infections and keep the population healthy. However, the greatest challenge is understanding the process of adopting self-care measures by individuals in different countries. In this research, we sought to understand the behavior of individuals who take self-protective action. We selected the risk homeostasis approach to identify relevant variables associated with the r…
On disasters evacuation modeling: From disruptive to slow-response decisions
Decision-making evacuation modeling for natural hazards has always been complex due to the uncertainty of variables affecting it. One of the most relevant existing assumptions for this kind of simulation is the use of sigmoid distributions (e.g., Rayleigh) to represent the evacuation times. We found some disadvantages in using this type of probability distribution for slow-response disasters (i.e., geological hazards applications), where there ma…
Computer Science (3 works) · Artificial Intelligence (2 works) · Engineering (2 works) · Geotechnical engineering (2 works) · Landslide (2 works) · Landslides and related hazards (2 works) · Action (physics (1 works) · Artificial neural network (1 works) · Bayesian network (1 works) · Computer security (1 works)