Spatial mapping of the provenance of storm dust: Application of data mining and ensemble modelling-Reference-Cited by-同舟云学术

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Spatial mapping of the provenance of storm dust: Application of data mining and ensemble modelling

Published:2020-03 Issue: Volume:233 Page:104716
ISSN:0169-8095
Container-title:Atmospheric Research
language:en
Short-container-title:Atmospheric Research

Author:

Gholami Hamid,Mohamadifar Aliakbar,Collins Adrian L.

Funder

Faculty of Agriculture and Natural Resources

University of Hormozgan

UK Biotechnology and Biological Sciences Research Council

Publisher

Elsevier BV

Subject

Atmospheric Science

Reference90 articles.

1. An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index;Ali;Atmos. Res.,2018

2. Dust storms and environmental health impacts;Almasi;J. Mid. East Appl. Sci. Technol. (JMEAST),2014

3. Assessment of the importance of gully erosion effective factors using Boruta algorithm and its spatial modeling and mapping using three machine learning algorithms;Amiri;Geoderma,2019

4. Gully erosion zonation mapping using integrated geographically weighted regression with certainty factor and random forest models in GIS;Arabameri;J. Environ. Manag.,2019

5. Statistical analysis of dust storms in the United Arab Emirates;Barbulescu;Atmos. Res.,2020

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