|
26641 |
The moderating role of trust in government adoption e-service during Covid-19 pandemic: health belief model perspective
Enthalten in International journal of information technology Bd. 15, 7.3.2023, Nr. 3, date:3.2023: 1545-1553
|
|
|
|
26642 |
The momentum operator on a union of intervals and the Fuglede conjecture
Enthalten in Sampling theory, signal processing, and data analysis Bd. 21, 10.11.2023, Nr. 2, date:12.2023: 1-25
|
|
|
|
26643 |
The most suitable mode decomposition technique for machine learning in meteorological time series prediction
Enthalten in Journal of earth system science Bd. 132, 12.5.2023, Nr. 2, date:6.2023: 1-27
|
|
|
|
26644 |
The Neuroimmune and Neurotoxic Fingerprint of Major Neurocognitive Psychosis or Deficit Schizophrenia: a Supervised Machine Learning Study
Enthalten in Neurotoxicity research Bd. 37, 8.1.2020, Nr. 3, date:3.2020: 753-771
|
|
|
|
26645 |
The nonlinear relationship between air quality and housing prices by machine learning
Enthalten in Environmental science and pollution research Bd. 30, 20.10.2023, Nr. 53, date:11.2023: 114375-114390
|
|
|
|
26646 |
The performance-interpretability trade-off: a comparative study of machine learning models
Enthalten in Journal of reliable intelligent environments Bd. 11, 2.12.2024, Nr. 1, date:3.2025: 1-15
|
|
|
|
26647 |
The performance of some machine learning approaches and a rich context model in student answer prediction
Enthalten in Research and practice in technology enhanced learning Bd. 16, 26.4.2021, Nr. 1, date:12.2021: 1-16
|
|
|
|
26648 |
The performance of VCS(volume, conductivity, light scatter) parameters in distinguishing latent tuberculosis and active tuberculosis by using machine learning algorithm
Enthalten in BMC infectious diseases Bd. 23, 16.12.2023, Nr. 1, date:12.2023: 1-9
|
|
|
|
26649 |
The perils of machine learning in designing new chemicals and materials
Enthalten in Nature machine intelligence Bd. 4, 22.4.2022, Nr. 4, date:4.2022: 314-315
|
|
|
|
26650 |
The potential evaluation of groundwater by integrating rank sum ratio (RSR) and machine learning algorithms in the Qaidam Basin
Enthalten in Environmental science and pollution research Bd. 30, 15.4.2023, Nr. 23, date:5.2023: 63991-64005
|
|
Administration
