Intelligent Recognition of Ore‐Forming Anomalies Based on Multisource Data Fusion: A Case Study of the Daqiao Mining Area, Gansu Province, China

Author:

Cai Huihui12,Chen Siqiong3,Xu Yongyang34ORCID,Li Zixuan3,Ran Xiangjin5,Wen Xingping6,Li Yongsheng1,Men Yanqing7

Affiliation:

1. China Geological Survey Development and Research Center Beijing China

2. China University of Geosciences Beijing China

3. School of Geography and Information Engineering China University of Geosciences Wuhan China

4. Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural Resources Shenzhen China

5. College of Earth Sciences Jilin University Jilin China

6. Faculty of Land and Resources Engineering Kunming University of Science and Technology Kunming China

7. Jinan Transportation Group Co., Ltd Jinan China

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

Reference36 articles.

1. Predicting dark matter halo formation in N-body simulations with deep regression networks

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3. The division of metallogenic prospective areas based on convolutional neural network model: A case study of the Daqiao gold polymetallic deposit;Cai H. H.;Geological Bulletin of China,2019

4. Prediction method of Tungsten‐molybdenum prospecting target area based on deep learning;Cai H. H.;Journal of Geo‐information Science,2019

5. Data-Driven Predictive Modeling of Mineral Prospectivity Using Random Forests: A Case Study in Catanduanes Island (Philippines)

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