Siamese network based prospecting prediction method: A case study from the Au deposit in the Chongli mineral concentrate area in Zhangjiakou, Hebei Province, China

被引:12
|
作者
Ding, Ke [1 ]
Xue, Linfu [1 ]
Ran, Xiangjin [1 ]
Wang, Jianbang [1 ]
Yan, Qun [1 ]
机构
[1] Jilin Univ, Coll Earth Sci, Changchun 130061, Peoples R China
关键词
Siamese network; Few -shot learning; Chongli mineral concentration area; Gold deposit; Prospecting prediction; DONGPING GOLD DEPOSIT; BIG DATA; INTEGRATION; ZIRCON;
D O I
10.1016/j.oregeorev.2022.105024
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
Supervised neural networks constitute an important research area for the intelligent prediction of locations for prospecting mineral deposits. Accurate training of a supervised neural network requires many training samples, something that is often difficult to obtain. This paper reports the use of geological, geochemical, and geophysical data by a Siamese network to overcome the problem of insufficient training samples, and implements a supervised deep learning prospecting prediction method based on the Siamese network. Intelligent prediction for gold deposits prospecting is carried out for the Chongli mineral concentrate area in Zhangjiakou, Hebei Province, China, and compared with the weight of evidence method and convolutional neural network model. The results show that:(a) the performance of the Siamese network model is no less than that of the convolutional neural network (CNN) model and better than that of the weight of evidence (WOE) method; (b) the gold prospective areas differentiated by the established models are strongly consistent with geological and metallogenic characteristics in the study area. This study suggests Siamese network model as an effective mineral prospectivity modeling tool. This method is also suitable for prospecting prediction using geoscience data in other areas.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Transfer learning and siamese neural network based identification of geochemical anomalies for mineral exploration: A case study from the Cu-Au deposit in the NW Junggar area of northern Xinjiang Province, China
    Wu, Bangcai
    Li, Xiaohui
    Yuan, Feng
    Li, He
    Zhang, Mingming
    [J]. JOURNAL OF GEOCHEMICAL EXPLORATION, 2022, 232
  • [2] CNN2D-SENet-Based Prospecting Prediction Method: A Case Study from the Cu Deposits in the Zhunuo Mineral Concentrate Area in Tibet
    Ding, Ke
    Xue, Linfu
    Ran, Xiangjin
    Wang, Jianbang
    Yan, Qun
    [J]. MINERALS, 2023, 13 (06)
  • [3] Mineral Prospectivity Prediction Based on Self-Supervised Contrastive Learning and Geochemical Data: A Case Study of the Gold Deposit in the Malanyu District, Hebei Province, China
    Miao, Qunfeng
    Wang, Pan
    Zhao, Hengqian
    Li, Zhibin
    Qi, Yunfei
    Mao, Jihua
    Li, Meiyu
    Tang, Guanglong
    [J]. NATURAL RESOURCES RESEARCH, 2024, 33 (04) : 1377 - 1391
  • [4] Mineral prospectivity prediction based on the dynamic relation model Atten-GCN: A case study of gold prospecting in the Yingfengjie area, Shaanxi province (northern China)
    Rui, Wang
    Linfu, Xue
    Yongsheng, Li
    Jianbang, Wang
    Qun, Yan
    Xiangjin, Ran
    [J]. Ore Geology Reviews, 2025, 176
  • [5] A Spatial Equilibrium Evaluation of Primary Education Services Based on Living Circle Models: A Case Study within the City of Zhangjiakou, Hebei Province, China
    Huang, An
    Xu, Yueqing
    Zhang, Yibin
    Lu, Longhui
    Liu, Chao
    Sun, Piling
    Liu, Qingguo
    [J]. LAND, 2022, 11 (11)
  • [6] Application of the multi-attribute anomaly model for prospecting potential at depth: A case study of the Haiyu Au deposit in the Jiaodong Gold Province, China
    Wang Jian
    Zhu Lixin
    Ma Shengming
    Tang Shixin
    Zhang Liangliang
    Zhou Weiwei
    [J]. JOURNAL OF GEOCHEMICAL EXPLORATION, 2019, 207
  • [7] The impact of groundwater recharge on land subsidence: a case study from the Cangzhou test area, Hebei Province, China
    Wang, Xin
    Luo, Zujiang
    Li, Zhao
    Zhao, Qian
    Dai, Jing
    [J]. HYDROGEOLOGY JOURNAL, 2023, 31 (03) : 813 - 825
  • [8] A hybrid coal prediction model based on grey Markov optimized by GWO - A case study of Hebei province in China
    Xu, Yan
    Lin, Tong
    Du, Pei
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2024, 235
  • [9] Oxygen fugacity, temperature and pressure estimation from mineral chemistry of the granodiorite porphyry from the Jilongshan Au-Cu deposit and the Baiguoshu prospecting area in SE Hubei Province: A guide for mineral exploration
    Samake, Bakaramoko
    Xu, Yao-Ming
    Jiang, Shao-Yong
    [J]. JOURNAL OF GEOCHEMICAL EXPLORATION, 2018, 184 : 136 - 149
  • [10] Improving resource utilization efficiency in China's mineral resource-based cities: A case study of Chengde, Hebei province
    Yu, Chenjian
    Li, Huiquan
    Jia, Xiaoping
    Li, Qiang
    [J]. RESOURCES CONSERVATION AND RECYCLING, 2015, 94 : 1 - 10