GA-XGBoost-based interpretable model for predicting molten iron yield of blast furnace

MEGN Kai, LIU Xiaojie, YI Fengyong, DUAN Yifan, CHEN Shujun, LIU Erhao

Metallurgical Industry Automation ›› 2024, Vol. 48 ›› Issue (6) : 108-121.

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Metallurgical Industry Automation ›› 2024, Vol. 48 ›› Issue (6) : 108-121. DOI: 10. 3969/ j. issn. 1000-7059. 2024. 06. 012
Artificial intelligence technique

 GA-XGBoost-based interpretable model for predicting molten iron yield of blast furnace

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{{article.zuoZheEn_L}}. {{article.title_en}}[J]. {{journal.qiKanMingCheng_EN}}, 2024, 48(6): 108-121 https://doi.org/10. 3969/ j. issn. 1000-7059. 2024. 06. 012

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Bimonthly, Started in 1976
CN 11-2067/TF
ISSN 1000-7059
Competent Authority: China lron & Steel Association
Sponsor: Automation Research and Design Institute of Metallurgical Industry Co., Ltd.
CISRI Boyuan Publishing Co.,Ltd.
Editor and Publisher: CISRI Boyuan Publishing Co.,Ltd.
Postal Code: 2-321
Foreign Distributed Code: BM5548
Address: No.76 Xueyuan Nanlu, Beijing 100081, China
Tel: 010-62182720, 62181013
www.yjzdh.com, www.chinamet.cn
E-mail: mia@chinamet.cn
International publication Name Code: YEZIES
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