Land subsidence susceptibility mapping: a new approach to improve decision stump classification (DSC) performance and combine it with four machine learning algorithms

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Publicat a:	Environmental Science and Pollution Research vol. 31, no. 10 (Feb 2024), p. 15443
Autor principal:	Zhao, Rui
Altres autors:	Arabameri, Alireza, Santosh, M.
Publicat:	Springer Nature B.V.
Matèries:	Risk management Classification Mapping Machine learning Subsidence Maps Learning algorithms Decision trees Accuracy Groundwater depletion Land subsidence Support vector machines Environmental degradation Root-mean-square errors Impact damage Impact analysis Algorithms Groundwater Risk reduction Semiarid zones Economic
Accés en línia:	Citation/Abstract Full Text - PDF
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