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Artikel 831 Towards the systematic reconnaissance of seismic signals from glaciers and ice sheets – Part 1: Event detection for cryoseismology
Enthalten in The Cryosphere Bd. 18, 2024, Nr. 4: 2061-2079. 19 S.
Online Ressource
Artikel 832 Recent warming trends of the Greenland ice sheet documented by historical firn and ice temperature observations and machine learning
Enthalten in The Cryosphere Bd. 18, 2024, Nr. 2: 609-631. 23 S.
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Artikel 833 An Intelligent Approach for Predicting Stock Market Movements in Emerging Markets Using Optimized Technical Indicators and Neural Networks
Enthalten in Economics / Journal articles Bd. 18, 2024, Nr. 1. 14 S.
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Artikel 834 Asset Pricing and Portfolio Investment Management Using Machine Learning: Research Trend Analysis Using Scientometrics
Enthalten in Economics / Journal articles Bd. 18, 2024, Nr. 1. 20 S.
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Artikel 835 Improving the Gaussianity of radar reflectivity departures between observations and simulations using symmetric rain rates
Enthalten in Atmospheric measurement techniques Bd. 17, 2024, Nr. 15: 4675-4686. 12 S.
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Artikel 836 TorchClim v1.0: a deep-learning plugin for climate model physics
Enthalten in Geoscientific model development Bd. 17, 2024, Nr. 14: 5459-5475. 17 S.
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Artikel 837 Transferability of machine-learning-based global calibration models for NO<sub>2</sub> and NO low-cost sensors
Enthalten in Atmospheric measurement techniques Bd. 17, 2024, Nr. 13: 3917-3931. 15 S.
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Artikel 838 Multivariate adjustment of drizzle bias using machine learning in European climate projections
Enthalten in Geoscientific model development Bd. 17, 2024, Nr. 11: 4689-4703. 15 S.
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Artikel 839 Atmospheric motion vector (AMV) error characterization and bias correction by leveraging independent lidar data: a simulation using an observing system simulation experiment (OSSE) and optical flow AMVs
Enthalten in Atmospheric measurement techniques Bd. 17, 2024, Nr. 10: 3103-3119. 17 S.
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Artikel 840 Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Enthalten in Geoscientific model development Bd. 17, 2024, Nr. 9: 4017-4029. 13 S.
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