|
25891 |
Predicting the efficiency of luminescent solar concentrators for solar energy harvesting using machine learning
Enthalten in Scientific reports Bd. 14, 20.2.2024, Nr. 1, date:12.2024: 1-10
|
|
|
|
25892 |
Predicting the elemental compositions of solid waste using ATR-FTIR and machine learning
Enthalten in Frontiers of environmental science & engineering Bd. 17, 30.4.2023, Nr. 10, date:10.2023: 1-14
|
|
|
|
25893 |
PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer’s Disease With machine learning: the PREVIEW study protocol
Enthalten in BMC neurology Bd. 23, 12.8.2023, Nr. 1, date:12.2023: 1-13
|
|
|
|
25894 |
Predicting the formation of fractionally doped perovskite oxides by a function-confined machine learning method
Enthalten in Communications materials Bd. 3, 6.7.2022, Nr. 1, date:12.2022: 1-10
|
|
|
|
25895 |
Predicting the impact of internet usage on students’ academic performance using machine learning techniques in Bangladesh perspective
Enthalten in Social network analysis and mining Bd. 14, 21.3.2024, Nr. 1, date:12.2024: 1-41
|
|
|
|
25896 |
Predicting the impact of yoga on chronic venous insufficiency: a machine learning approach using Naive Bayes classifier and optimization systems
Enthalten in Journal of ambient intelligence and humanized computing Bd. 16, 4.1.2025, Nr. 1, date:1.2025: 109-131
|
|
|
|
25897 |
Predicting the in-game status in soccer with machine learning using spatiotemporal player tracking data
Enthalten in Scientific reports Bd. 12, 29.9.2022, Nr. 1, date:12.2022: 1-10
|
|
|
|
25898 |
Predicting the level of anemia among Ethiopian pregnant women using homogeneous ensemble machine learning algorithm
Enthalten in BMC medical informatics and decision making Bd. 22, 22.9.2022, Nr. 1, date:12.2022: 1-11
|
|
|
|
25899 |
Predicting the level of autism and improvement rate from assessment dataset using machine learning techniques
Enthalten in International journal of information technology Bd. 15, 6.3.2023, Nr. 3, date:3.2023: 1647-1652
|
|
|
|
25900 |
Predicting the magnitude of injection-induced earthquakes using machine learning techniques
Enthalten in Natural hazards Bd. 118, 23.5.2023, Nr. 1, date:8.2023: 545-570
|
|
Administration
