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Luc Cimusa Kulimushi

Biographic Data

ID7575552
NAMELuc Cimusa Kulimushi
GIVEN NAMESLuc Cimusa
FAMILY NAMEKulimushi
SIGNATUREKULIMUSHI L C
AFFILIATIONSUniversity of Lay Adventists of Kigali
ORCID0000-0003-2228-0042
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS0
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2023
H-INDEX0
  • Performance evaluation of machine learning algorithms to assess soil erosion in Mediterranean farmland

    Open Access•Safwan Mohammed, Ali Jouhra et al.•ARTICLE•Land Degradation and Development•2023

    The development of new techniques, such as machine learning (ML), can provide better insight into the processes and drivers of soil erosion and runoff. However, the performance of these techniques to assess soil erosion in agricultural landscapes is poorly understood. The aim of this study was to evaluate the performance of four machine learning algorithms, generalized linear model (GLM), Random Forest (RF), elastic net regression (EN) and multip…

  • Identification of erosion-prone areas using morphometric parameters, land use land cover and multi-criteria decision-making method

    Open Access•Paolenmang Haokip, Md Abdullah Khan et al.•ARTICLE•Environment Development and…•2022

No prominent works on this page.

  • Identification of erosion-prone areas using morphometric parameters, land use land cover and multi-criteria decision-making method

    Open Access•Paolenmang Haokip, Md Abdullah Khan et al.•ARTICLE•Environment Development and…•2022

  • Performance evaluation of machine learning algorithms to assess soil erosion in Mediterranean farmland

    Open Access•Safwan Mohammed, Ali Jouhra et al.•ARTICLE•Land Degradation and Development•2023

    The development of new techniques, such as machine learning (ML), can provide better insight into the processes and drivers of soil erosion and runoff. However, the performance of these techniques to assess soil erosion in agricultural landscapes is poorly understood. The aim of this study was to evaluate the performance of four machine learning algorithms, generalized linear model (GLM), Random Forest (RF), elastic net regression (EN) and multip…

Environmental Science (2 works) · Erosion (2 works) · Geography (2 works) · Geology (2 works) · Soil erosion and sediment transport (2 works) · Algorithm (1 work) · Cartography (1 work) · Digital elevation model (1 work) · Drainage basin (1 work) · Drainage density (1 work)

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