Lithologic mapping using Random Forests applied to geophysical and remote-sensing data: A demonstration study from the Eastern Goldfields of Australia

S Kuhn, MJ Cracknell, AM Reading - Geophysics, 2018 - library.seg.org
ABSTRACT The Eastern Goldfields of Western Australia is one of the world's premier gold-
producing regions; however, large areas of prospective bedrock are under cover and lack …

Multi-element geochemical data mining: implications for block boundaries and deposit distributions in South China

W Liu, Q Lü, Z Cheng, G Xing, J Yan, L Yuan… - Ore Geology Reviews, 2021 - Elsevier
To explore the macroscopic characteristics of geological block boundaries, Mesozoic
magmatic rocks, and various ore deposit distributions in South China, we processed large …

Identifying geochemical anomalies associated with Au–Cu mineralization using multifractal and artificial neural network models in the Ningqiang district, Shaanxi …

J Zhao, S Chen, R Zuo - Journal of Geochemical Exploration, 2016 - Elsevier
The Ningqiang district, which is located in the northwestern margin of the Yangtze Platform,
contains the richest supply of Cu and Au mineral resources in Shaanxi Province, China. The …

Lithological mapping using a convolutional neural network based on stream sediment geochemical survey data

X Wang, R Zuo, Z Wang - Natural Resources Research, 2022 - Springer
Mapping of lithological units is a significant challenge for geological tasks. Stream sediment
geochemical survey data contain abundant geological information that can help delineate …

Geological mapping of basalt using stream sediment geochemical data: Case study of covered areas in Jining, Inner Mongolia, China

YZ Ge, ZJ Zhang, QM Cheng, GP Wu - Journal of Geochemical Exploration, 2022 - Elsevier
Multidisciplinary exploration data have been widely and successfully applied when using
machine learning methods to conduct geological mapping. However, in covered areas such …

Artificial neural network for acid sulfate soil mapping: Application to the Sirppujoki River catchment area, south-western Finland

A Beucher, P Österholm, A Martinkauppi, P Edén… - Journal of Geochemical …, 2013 - Elsevier
In Finland, acid sulfate (AS) soils constitute a major environmental issue. These soils leach
considerable amounts of metals into watercourses, causing severe ecological damage. As …

Identification of intrusive lithologies in volcanic terrains in British Columbia by machine learning using random forests: The value of using a soft classifier

S Kuhn, MJ Cracknell, AM Reading, S Sykora - Geophysics, 2020 - library.seg.org
Identifying the location of intrusions is a key component in exploration for porphyry
Cu±Mo±Au deposits. In typical porphyry terrains, in the absence of outcrop, intrusions can …

基于t-SNE 降维算法的区域化探数据中地质体空间分布信息可视化: 以英格兰西南部为例

陈军林, 闫岩, 彭润民 - 地质科技通报, 2021 - dzkjqb.cug.edu.cn
区域化探数据中包含了丰富的地质信息, 提取出蕴含在这些数据中的地质体空间分布信息,
对于区域地质研究和找矿勘查具有重要意义. 区域化探数据通常包括数十个元素, 属于高维数据 …

Image processing and machine learning applications in mining industry: Mine 4.0

H Ouanan - … on Intelligent Systems and Advanced Computing …, 2019 - ieeexplore.ieee.org
Recently, Image processing (IP) and Machine learning (ML) algorithms have been
successfully used in a wide variety of industry sectors. In this paper, we first provide mining …

Artificial neural network for mapping and characterization of acid sulfate soils: Application to Sirppujoki River catchment, southwestern Finland

A Beucher, R Siemssen, S Fröjdö, P Österholm… - Geoderma, 2015 - Elsevier
Acid sulfate (as) soil mapping constitutes a fundamental step in order to plan and carry out
effective mitigation at catchment scale. The main goal of this study was to assess the use of …