| 公開日期 | 標題 | 作者 | 來源出版物 | scopus | WOS | 全文 |
| 2024 | An Advanced Soil Classification Method Employing the Random Forest Technique in Machine Learning | Liu, Chih-Yu ; Ku, Cheng-Yu ; Wu, Ting-Yuan; Ku, Yun-Cheng | APPLIED SCIENCES-BASEL | | | |
| 2024/11/11 | Evaluation of liquefaction potential in central Taiwan using random forest method | Liu, Chih-Yu ; Ku, Cheng-Yu ; Chiu, Yu-Jia ; Wu, Ting-Yuan | SCIENTIFIC REPORTS | | | |
| 2022 | Predicting Heavy Metal Concentrations in Shallow Aquifer Systems Based on Low-Cost Physiochemical Parameters Using Machine Learning Techniques | Thi-Minh-Trang Huynh; Ni, Chuen-Fa; Su, Yu-Sheng ; Vo-Chau-Ngan Nguyen; Lee, I-Hsien; Lin, Chi-Ping; Hoang-Hiep Nguyen | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH | | 0 | |
| 2021 | Predictive models for the effect of environmental factors on the abundance of Vibrio parahaemolyticus in oyster farms in Taiwan using extreme gradient boosting | Ndraha, Nodali; Hsiao, Hsin-, I ; Hsieh, Yi-Zeng ; Pradhan, Abani K. | FOOD CONTROL | | 8 | |
