Objective diagnosis of machine learning method applicability to land comprehensive carrying capacity evaluation: A case study based on integrated RF and DPSIR models

[Display omitted] •The machine learning approach was applicable in LCCC evaluation.•The influence subsystem was enhanced in DPSIR while the drive subsystem was weakened.•RF was suitable for use with the multidimensional spatial heterogeneity index system.•The complexity and nonlinear characteristics...

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Vydané v:	Ecological indicators Ročník 151; s. 110338
Hlavní autori:	Hu, Wenmin, Zhang, Shibo, Fu, Yushan, Jia, Guanyu, Yang, Ruihan, Shen, Shouyun, Li, Yi, Li, Guo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.07.2023 Elsevier
Predmet:	case studies DPSIR model Land comprehensive carrying capacity Land use principal component analysis Random forest spatial variation Support vector machine support vector machines sustainable development Land comprehensive carrying capacity Random forest Support vector machine Land use DPSIR model
ISSN:	1470-160X, 1872-7034
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