Výsledky vyhledávání - "Francky Fouedjio"

Akademický článek

Locally varying geostatistical machine learning for spatial prediction

Autor: Francky Fouedjio, Emet Arya

Publikováno v: Artificial Intelligence in Geosciences, Vol 5, Iss , Pp 100081- (2024)

Machine learning methods dealing with the spatial auto-correlation of the response variable have garnered significant attention in the context of spatial prediction. Nonetheless, under these methods, the relationship between the response variable and

Externí odkaz: https://doaj.org/article/6be179e74dc84b73acc6b65f057d5dd0

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Akademický článek

Geostatistical semi-supervised learning for spatial prediction

Autor: Francky Fouedjio, Hassan Talebi

Publikováno v: Artificial Intelligence in Geosciences, Vol 3, Iss , Pp 162-178 (2022)

Geoscientists are increasingly tasked with spatially predicting a target variable in the presence of auxiliary information using supervised machine learning algorithms. Typically, the target variable is observed at a few sampling locations due to the

Externí odkaz: https://doaj.org/article/88d701e5685b4454879011f8db170fb5

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Akademický článek

Classification random forest with exact conditioning for spatial prediction of categorical variables

Autor: Francky Fouedjio

Publikováno v: Artificial Intelligence in Geosciences, Vol 2, Iss , Pp 82-95 (2021)

Machine learning methods are increasingly used for spatially predicting a categorical target variable when spatially exhaustive predictor variables are available within the study region. Even though these methods exhibit competitive spatial predictio

Externí odkaz: https://doaj.org/article/d016cfdd77754069a3b4beb261a2125e

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Akademický článek

Random forest for spatial prediction of censored response variables

Autor: Francky Fouedjio

Publikováno v: Artificial Intelligence in Geosciences, Vol 2, Iss , Pp 115-127 (2021)

The spatial prediction of a continuous response variable when spatially exhaustive predictor variables are available within the region under study has become ubiquitous in many geoscience fields. The response variable is often subject to detection li

Externí odkaz: https://doaj.org/article/e22b52133c3f4552b1d431b8078e01d2

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Akademický článek

Exact Conditioning of Regression Random Forest for Spatial Prediction

Autor: Francky Fouedjio

Publikováno v: Artificial Intelligence in Geosciences, Vol 1, Iss , Pp 11-23 (2020)

Regression random forest is becoming a widely-used machine learning technique for spatial prediction that shows competitive prediction performance in various geoscience fields. Like other popular machine learning methods for spatial prediction, regre

Externí odkaz: https://doaj.org/article/5b3e1487e8424e5ba61bf2b7352e41f7

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Conditional simulation of categorical spatial variables using Gibbs sampling of a truncated multivariate normal distribution subject to linear inequality constraints

Autor: Liang Yang, Francky Fouedjio, Yizheng Wang, Jef Caers, Céline Scheidt

Publikováno v: Stochastic Environmental Research and Risk Assessment. 35:457-480

This paper introduces a method to generate conditional categorical simulations, given an ensemble of partially conditioned (or unconditional) categorical simulations derived from any simulation process. The proposed conditioning method relies on impl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4b97d6aee7e708ddae2502d756f34088
https://doi.org/10.1007/s00477-020-01925-7

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