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Learning Regionalization Using Accurate Spatial Cost Gradients Within a Differentiable High‐Resolution Hydrological Model: Application to the French Mediterranean Region
Published 2024-11-01“…This paper introduces a Hybrid Data Assimilation and Parameter Regionalization (HDA‐PR) approach incorporating learnable regionalization mappings, based on either multi‐linear regression or artificial neural networks (ANNs), into a differentiable hydrological model. …”
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102
Identification and validation of ANXA3 and SOCS3 as biomarkers for acute myocardial infarction related to sphingolipid metabolism
Published 2025-08-01“…Further analyses included artificial neural networks (ANN), enrichment analysis, immune infiltration, drug prediction, and molecular docking. …”
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103
Strategic optimization of engine performance and emissions with bio-hydrogenated diesel and biodiesel: A RVEA-GRNNs framework
Published 2024-12-01“…Using a single-cylinder diesel engine from POLAWAT ENGINE Company Limited, we evaluated different bio-hydrogenated diesel and biodiesel blends, optimizing their composition through the Reference Vector Guided Evolutionary Algorithm with a surrogate objective function via Generalized Regression Neural Networks. …”
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104
A Domain-Specific Pretrained Model for Detecting Malignant and Premalignant Ocular Surface Tumors: A Multicenter Model Development and Evaluation Study
Published 2025-01-01“…However, training traditional convolutional neural networks (CNNs) for this task presents challenges due to the lack of large, well-annotated datasets containing OST images labeled according to histopathological results. …”
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105
Numerical thermodynamic-economic study and machine learning-based optimization of an innovative biogas-driven integrated power plant combined with sustainable liquid CO2 and liquid...
Published 2025-05-01“…Hence, a machine learning algorithm is implemented using artificial neural networks combined with the NSGA-II method for multi-criteria optimization, focusing on exergy efficiency, net present value, and products' sum unit cost as objective functions. …”
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