Search alternatives:
processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
encoding algorithm » finding algorithm (Expand Search), cosine algorithm (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
data processing » image processing (Expand Search)
data encoding » data including (Expand Search), data according (Expand Search), data recording (Expand Search)
processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
encoding algorithm » finding algorithm (Expand Search), cosine algorithm (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
data processing » image processing (Expand Search)
data encoding » data including (Expand Search), data according (Expand Search), data recording (Expand Search)
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Data Sheet 1_Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model.docx
Published 2025“…Considering the increased detection range of EDARM and the requirements for computational efficiency, this paper presents a 2.5-dimensional (2.5D) finite element method (FEM). By leveraging the symmetry of simulated signals in the spectral domain, the algorithm reduces computation time by 50%, significantly enhancing computational efficiency while preserving accuracy. …”
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Hyperparameter and model configurations.
Published 2025“…The five interconnected modules constituting the architecture include (i) multi-source data collection using RESTful APIs; (ii) weighted preprocessing pipelines using tokenization, lemmatization, and normalization; (iii) Adam algorithm-optimized model training and cross-entropy loss minimization-based training; (iv) adaptive real-time processing using dynamic window segmentation; and (v) an ongoing refinement loop using continuous user inputs, triggered by a feedback mechanism. …”
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Performance in best and worst case scenarios.
Published 2025“…The five interconnected modules constituting the architecture include (i) multi-source data collection using RESTful APIs; (ii) weighted preprocessing pipelines using tokenization, lemmatization, and normalization; (iii) Adam algorithm-optimized model training and cross-entropy loss minimization-based training; (iv) adaptive real-time processing using dynamic window segmentation; and (v) an ongoing refinement loop using continuous user inputs, triggered by a feedback mechanism. …”
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Datasets and experimental settings.
Published 2025“…The five interconnected modules constituting the architecture include (i) multi-source data collection using RESTful APIs; (ii) weighted preprocessing pipelines using tokenization, lemmatization, and normalization; (iii) Adam algorithm-optimized model training and cross-entropy loss minimization-based training; (iv) adaptive real-time processing using dynamic window segmentation; and (v) an ongoing refinement loop using continuous user inputs, triggered by a feedback mechanism. …”