Contribution of Random Forest and Deep Neural Network Algorithms with Environmental Covariates for the Spatial SOC Stock Modelling
Institutions
Aix-Marseille Université (FR)
Centre de Recherche et d’Enseignement de Géosciences de l’Environnement (FR)
Centre d'Études et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (FR)
Étude des Structures, des Processus d’Adaptation et des Changements de l’Espace (FR)
Publication Details
Journal
SPIRE - Sciences Po Institutional REpository
Published
2025-05-22
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
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article
Contribution of Random Forest and Deep Neural Network Algorithms with Environmental Covariates for the Spatial SOC Stock Modelling
Journal
SPIRE - Sciences Po Institutional REpository
Topics
Stock Market Forecasting Methods
article
Contribution of Random Forest and Deep Neural Network Algorithms with Environmental Covariates for the Spatial SOC Stock Modelling
article en
Abstract
No abstract available for this paper.
Publication Tag
SPIRE - Sciences Po Institutional REpository
Institutions
Aix-Marseille Université (FR), Centre de Recherche et d’Enseignement de Géosciences de l’Environnement (FR), Centre d'Études et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (FR), Étude des Structures, des Processus d’Adaptation et des Changements de l’Espace (FR)
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Contribution of Random Forest and Deep Neural Network Algorithms with Environmental Covariates for the Spatial SOC Stock Modelling · SPIRE - Sciences Po Institutional REpository (2025) | TGRS Research Map | TGRS