|
16611 |
Using machine learning-based algorithms to construct cardiovascular risk prediction models for Taiwanese adults based on traditional and novel risk factors
Enthalten in BMC medical informatics and decision making Bd. 24, 22.7.2024, Nr. 1, date:12.2024: 1-8
|
|
|
|
16612 |
Using meta-learning for automated algorithms selection and configuration: an experimental framework for industrial big data
Enthalten in Journal of Big Data Bd. 9, 29.4.2022, Nr. 1, date:12.2022: 1-20
|
|
|
|
16613 |
Using metaheuristic algorithms to optimize a mixed model-based ground-motion prediction model and associated variance components
Enthalten in Journal of seismology Bd. 26, 4.5.2022, Nr. 3, date:6.2022: 483-498
|
|
|
|
16614 |
Using multi-objective evolutionary algorithms for single-objective constrained and unconstrained optimization
Enthalten in Annals of operations research Bd. 240, 22.9.2015, Nr. 1, date:5.2016: 217-250
|
|
|
|
16615 |
Using multi-objective evolutionary algorithms to predict the parameters that determine membrane resonance in a biophysical model of bursting neurons
Enthalten in BMC neuroscience Bd. 15, 21.7.2014, Nr. 1, date:7.2014: 1-2
|
|
|
|
16616 |
Using multivariate adaptive regression splines and extremely randomized trees algorithms to predict dust events frequency around an international wetland and prioritize its drivers
Enthalten in Environmental monitoring and assessment Bd. 193, 22.6.2021, Nr. 7, date:7.2021: 1-21
|
|
|
|
16617 |
Using Nondeterminism to Design Efficient Deterministic Algorithms
Enthalten in Algorithmica Bd. 40, 16.4.2004, Nr. 2, date:10.2004: 83-97
|
|
|
|
16618 |
Using of Genetic Algorithms for Adaptive Filter Selection in Special-Purpose Systems
Enthalten in Russian journal of general chemistry Bd. 91, 17.1.2022, Nr. 12, date:12.2021: 2734-2736
|
|
|
|
16619 |
Using Optimized Deep Learning to Predict Daily Streamflow: A Comparison to Common Machine Learning Algorithms
Enthalten in Water resources management Bd. 36, 17.1.2022, Nr. 2, date:1.2022: 699-716
|
|
|
|
16620 |
Using primary care data to evaluate the 10-year cost-effectiveness of cardiovascular disease risk algorithms in patients with serious mental illness: a patient level simulation
Enthalten in Trials Bd. 16, 16.11.2015, Nr. 2, date:12.2015: 1
|
|
Administration
