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Yuxiu Liu, Xing Yuan, Yang Jiao, Peng Ji, Chaoqun Li and Xindai An
Integrating numerical weather forecasts that provide ensemble precipitation forecasts, land surface hydrological modeling that resolves surface and subsurface hydrological processes, and artificial intelligence techniques that correct the forecast bias, ...
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Seoro Lee, Jonggun Kim, Joo Hyun Bae, Gwanjae Lee, Dongseok Yang, Jiyeong Hong and Kyoung Jae Lim
Accurate prediction of dam inflows is essential for effective water resource management and dam operation. In this study, we developed a multi-inflow prediction ensemble (MPE) model for dam inflow prediction using auto-sklearn (AS). The MPE model is desi...
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Khrystyna Lipianina-Honcharenko, Carsten Wolff, Anatoliy Sachenko, Ivan Kit and Diana Zahorodnia
Anthropogenic disasters pose a challenge to management in the modern world. At the same time, it is important to have accurate and timely information to assess the level of danger and take appropriate measures to eliminate disasters. Therefore, the purpo...
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Khrystyna Zub, Pavlo Zhezhnych and Christine Strauss
In this paper, we investigate the methods used to evaluate the admission chances of higher education institutions? (HEI) entrants as a crucial factor that directly influences the admission efficiency, quality of education results, and future students? li...
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Jingyun Gui, Ignacio Pérez-Rey, Miao Yao, Fasuo Zhao and Wei Chen
Spatial landslide susceptibility assessment is a fundamental part of landslide risk management and land-use planning. The main objective of this study is to apply the Credal Decision Tree (CDT), adaptive boosting Credal Decision Tree (AdaCDT), and random...
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