文献
J-GLOBAL ID:202202255956576501
整理番号:22A0805899
鉱物探査性のためのファジィ森林機械学習予測モデル:南西インド海嶺48.7°E-50.5°Eの事例研究【JST・京大機械翻訳】
Fuzzy Forest Machine Learning Predictive Model for Mineral Prospectivity: A Case Study on Southwest Indian Ridge 48.7°E-50.5°E
著者 (9件):
Liu Lushi
(College of Geo-Exploration Science and Technology, Jilin University, Changchun, China)
,
Liu Lushi
(Key Laboratory of Submarine Geosciences, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China)
,
Lu Jilong
(College of Geo-Exploration Science and Technology, Jilin University, Changchun, China)
,
Tao Chunhui
(College of Geo-Exploration Science and Technology, Jilin University, Changchun, China)
,
Tao Chunhui
(Key Laboratory of Submarine Geosciences, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China)
,
Liao Shili
(Key Laboratory of Submarine Geosciences, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China)
,
Su Cheng
(Institute for Geography and Spatial Information, School of Earth Sciences, Zhejiang University, Hangzhou, China)
,
Huang Nan
(Key Laboratory of Submarine Geosciences, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China)
,
Xu Xing
(School of Oceanography, Shanghai Jiaotong University, Shanghai, China)
資料名:
Natural Resources Research
(Natural Resources Research)
巻:
31
号:
1
ページ:
99-116
発行年:
2022年
JST資料番号:
W0688A
ISSN:
1520-7439
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)