Improving atmospheric corrosion prediction through key environmental factor identification by random forest-based model-Reference-Cited by-同舟云学术

Improving atmospheric corrosion prediction through key environmental factor identification by random forest-based model

Published:2021-01 Issue: Volume:178 Page:109084
ISSN:0010-938X
Container-title:Corrosion Science
language:en
Short-container-title:Corrosion Science

Author:

Zhi Yuanjie,Jin Zhihui,Lu Lin,Yang Tao,Zhou Deyun,Pei Zibo,Wu Dequan,Fu Dongmei,Zhang Dawei,Li Xiaogang

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

General Materials Science,General Chemical Engineering,General Chemistry

Reference59 articles.

1. Atmospheric corrosion of magnesium alloys: inﬂuence of temperature, relative humidity, and chloride deposition;LeBozec;Corrosion,2004

2. Influence of temperature and relative humidity on the atmospheric corrosion of zinc in Field exposures and laboratory environments by atmospheric corrosion monitor;Wang;Int. J. Electrochem. Sci.,2015

3. Atmospheric corrosion eﬀ ;ects of HNO3—inﬂuence of temperature and relative humidity on laboratory-exposed copper;Samie;Atmos. Environ.,2007

4. Evaluation of corrosivity in atmospheric environment by ACM (atmospheric corrosion monitor) type corrosion sensor;Shinohara;Mater. Sci. Forum,2005

5. Inﬂuence of environmental factors on atmospheric corrosion in dynamic environment;Cai;Corros. Sci.,2018

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