Using random forest for the risk assessment of coal-floor water inrush in Panjiayao Coal Mine, northern China-Reference-Cited by-同舟云学术

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Using random forest for the risk assessment of coal-floor water inrush in Panjiayao Coal Mine, northern China

Published:2018-04-13 Issue:7 Volume:26 Page:2327-2340
ISSN:1431-2174
Container-title:Hydrogeology Journal
language:en
Short-container-title:Hydrogeol J

Author:

Zhao Dekang,Wu Qiang,Cui Fangpeng,Xu Hua,Zeng Yifan,Cao Yufei,Du Yuanze

Funder

Innovation Research Team Program of Ministry of Education

China National Natural Science Foundation

China National Scientific and Technical Support Program

Natural Science Foundation of Beijing Municipality

Fundamental Research Funds for the Central Universities

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Water Science and Technology

Link

http://link.springer.com/article/10.1007/s10040-018-1767-5/fulltext.html

Reference45 articles.

1. Adam E, Mutanga O, Odindi J, Abdelrahman EM (2014) Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector machines classifiers. Int J Remote Sens 35(10):3440–3458

2. Bonissone P, Cadenas JM, Garrido MC, Díaz-Valladares RA (2010) A fuzzy random forest. Int J Approx Reason 51(7):729–747

3. Boulesteix A, Janitza S, Kruppa J, König IR (2012) Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics. WIREs Data Mining Knowl Discov 2(6):493–507

4. Breiman L (2001) Random forest. Mach Learn 45:5–32

5. Breiman L, Friedman JH, Olsen RA, Stone CJ (1984) Classification and regression trees. Wadsworth, Belmont, CA

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