Found: 21
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Site suitability for Aromatic Rice cultivation by integrating Geo-spatial and Machine learning algorithms in Kaliyaganj C.D. block, India.
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- Artificial Intelligence in Geosciences, 2021, p. 179, doi. 10.1016/j.aiig.2022.03.001
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Arriving at estimates of a rate and state fault friction model parameter using Bayesian inference and Markov chain Monte Carlo.
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- Artificial Intelligence in Geosciences, 2021, p. 171, doi. 10.1016/j.aiig.2022.02.003
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Flood susceptibility assessment using artificial neural networks in Indonesia.
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- Artificial Intelligence in Geosciences, 2021, p. 215, doi. 10.1016/j.aiig.2022.03.002
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Application of neural network to speed-up equilibrium calculations in compositional reservoir simulation.
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- Artificial Intelligence in Geosciences, 2021, p. 202, doi. 10.1016/j.aiig.2022.03.004
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Unilateral Alignment: An interpretable machine learning method for geophysical logs calibration.
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- Artificial Intelligence in Geosciences, 2021, p. 192, doi. 10.1016/j.aiig.2022.02.006
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Sparse inversion-based seismic random noise attenuation via self-paced learning.
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- Artificial Intelligence in Geosciences, 2021, p. 223, doi. 10.1016/j.aiig.2022.03.003
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Deep convolutional autoencoders as generic feature extractors in seismological applications.
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- Artificial Intelligence in Geosciences, 2021, p. 96, doi. 10.1016/j.aiig.2021.12.002
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Enhancing lithofacies machine learning predictions with gamma-ray attributes for boreholes with limited diversity of recorded well logs.
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- Artificial Intelligence in Geosciences, 2021, p. 148, doi. 10.1016/j.aiig.2022.02.007
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Towards a fully data-driven prospectivity mapping methodology: A case study of the Southeastern Churchill Province, Québec and Labrador.
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- Artificial Intelligence in Geosciences, 2021, p. 128, doi. 10.1016/j.aiig.2022.02.002
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Random forest for spatial prediction of censored response variables.
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- Artificial Intelligence in Geosciences, 2021, p. 115, doi. 10.1016/j.aiig.2022.02.001
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Hydrocarbon detections using multi-attributes based quantum neural networks in a tight sandstone gas reservoir in the Sichuan Basin, China.
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- Artificial Intelligence in Geosciences, 2021, p. 107, doi. 10.1016/j.aiig.2022.02.004
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Data-driven approaches for time series prediction of daily production in the Sulige tight gas field, China.
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- Artificial Intelligence in Geosciences, 2021, p. 165, doi. 10.1016/j.aiig.2022.02.005
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- Article
Classification random forest with exact conditioning for spatial prediction of categorical variables.
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- Artificial Intelligence in Geosciences, 2021, p. 82, doi. 10.1016/j.aiig.2021.11.003
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Microleveling aerogeophysical data using deep convolutional network and MoG-RPCA.
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- Artificial Intelligence in Geosciences, 2021, p. 20, doi. 10.1016/j.aiig.2021.08.003
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Wavefield solutions from machine learned functions constrained by the Helmholtz equation.
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- Artificial Intelligence in Geosciences, 2021, p. 11, doi. 10.1016/j.aiig.2021.08.002
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Machine learning-based prediction of trace element concentrations using data from the Karoo large igneous province and its application in prospectivity mapping.
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- Artificial Intelligence in Geosciences, 2021, p. 60, doi. 10.1016/j.aiig.2021.11.002
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Capsule network-based approach for estimating grassland coverage using time series data from enhanced vegetation index.
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- Artificial Intelligence in Geosciences, 2021, p. 26, doi. 10.1016/j.aiig.2021.08.001
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Rapid identification of high-quality marine shale gas reservoirs based on the oversampling method and random forest algorithm.
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- Artificial Intelligence in Geosciences, 2021, p. 76, doi. 10.1016/j.aiig.2021.12.001
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- Article
Near-surface velocity inversion from Rayleigh wave dispersion curves based on a differential evolution simulated annealing algorithm.
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- Artificial Intelligence in Geosciences, 2021, p. 35, doi. 10.1016/j.aiig.2021.10.001
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- Article
The potential of self-supervised networks for random noise suppression in seismic data.
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- Artificial Intelligence in Geosciences, 2021, p. 47, doi. 10.1016/j.aiig.2021.11.001
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The benefits and dangers of using artificial intelligence in petrophysics.
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- Artificial Intelligence in Geosciences, 2021, p. 1, doi. 10.1016/j.aiig.2021.04.001
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