Kefa Zhou
Biographic Data
| ID | 9807098 |
|---|---|
| NAME | Kefa Zhou |
| GIVEN NAMES | Kefa |
| FAMILY NAME | Zhou |
| SIGNATURE | ZHOU K |
| AFFILIATIONS | Xinjiang Institute of Ecology and Geography |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Research on Global Off-Road Path Planning Based on Improved A* Algorithm
In field driving activities, off-road areas usually lack existing paths that can be directly driven on by ground vehicles, but their surface environments can still satisfy the planning and passage requirements of some off-road vehicles. Additionally, the existing path planning methods face limitations in complex field environments characterized by undulating terrains and diverse land cover types. Therefore, this study introduces an improved A* al…
Mapping Mineral Prospectivity Using a Hybrid Genetic Algorithm–Support Vector Machine (GA–SVM) Model
Machine learning (ML) as a powerful data-driven method is widely used for mineral prospectivity mapping. This study employs a hybrid of the genetic algorithm (GA) and support vector machine (SVM) model to map prospective areas for Au deposits in Karamay, northwest China. In the proposed method, GA is used as an adaptive optimization search method to optimize the SVM parameters that result in the best fitness. After obtaining evidence layers from …
No prominent works on this page.
Mapping Mineral Prospectivity Using a Hybrid Genetic Algorithm–Support Vector Machine (GA–SVM) Model
Machine learning (ML) as a powerful data-driven method is widely used for mineral prospectivity mapping. This study employs a hybrid of the genetic algorithm (GA) and support vector machine (SVM) model to map prospective areas for Au deposits in Karamay, northwest China. In the proposed method, GA is used as an adaptive optimization search method to optimize the SVM parameters that result in the best fitness. After obtaining evidence layers from …
Research on Global Off-Road Path Planning Based on Improved A* Algorithm
In field driving activities, off-road areas usually lack existing paths that can be directly driven on by ground vehicles, but their surface environments can still satisfy the planning and passage requirements of some off-road vehicles. Additionally, the existing path planning methods face limitations in complex field environments characterized by undulating terrains and diverse land cover types. Therefore, this study introduces an improved A* al…
Algorithm (2 works) · Artificial Intelligence (2 works) · Computer Science (2 works) · Control and Dynamics of Mobile Robots (1 work) · Data mining (1 work) · Genetic algorithm (1 work) · Geochemistry and Geologic Mapping (1 work) · Geology (1 work) · Geomorphology (1 work) · Machine learning (1 work)