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16651 |
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
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16652 |
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
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16653 |
Using sentinel-2 satellite images and machine learning algorithms to predict tropical pasture forage mass, crude protein, and fiber content
Enthalten in Scientific reports Bd. 14, 15.4.2024, Nr. 1, date:12.2024: 1-14
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16654 |
Using simulated execution in verifying distributed algorithms
Enthalten in International journal on software tools for technology transfer Bd. 6, 6.4.2004, Nr. 1, date:7.2004: 67-76
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16655 |
Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms
Enthalten in BMC bioinformatics Bd. 18, 18.3.2017, Nr. 1, date:12.2017: 1-12
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16656 |
USING SMOS PASSIVE MICROWAVE DATA TO DEVELOP SMAP FREEZE/THAW ALGORITHMS ADAPTED FOR THE CANADIAN SUBARCTIC
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XL-1/W5, 2015: 365-368
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16657 |
Using sound to understand protein sequence data: new sonification algorithms for protein sequences and multiple sequence alignments
Enthalten in BMC bioinformatics Bd. 22, 23.9.2021, Nr. 1, date:12.2021: 1-17
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16658 |
Using stochastic algorithms for constraining compartmental and markov channel models
Enthalten in BMC neuroscience Bd. 10, 13.7.2009, Nr. 1, date:9.2009: 1
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16659 |
Using the artificial bee colony technique to optimize machine learning algorithms in estimating the mature weight of camels
Enthalten in Tropical animal health and production Bd. 55, 17.2.2023, Nr. 2, date:4.2023: 1-10
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16660 |
Using the Hybrid Simulated Annealing-M5 Tree Algorithms to Extract the If-Then Operation Rules in a Single Reservoir
Enthalten in Water resources management Bd. 33, 2.8.2019, Nr. 10, date:8.2019: 3655-3672
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