Identification of geochemical anomalies related to mineralization: A case study from porphyry copper deposits in the Qulong-Jiama mining district of Tibet, China

Data-driven Mineral Prospectivity Mapping by Joint Application of Unsupervised Convolutional Auto-encoder Network and Supervised Convolutional Neural Network

(2021) Shuai Zhang et al.   Natural Resources Research

Detection of Multivariate Geochemical Anomalies Using the Bat-Optimized Isolation Forest and Bat-Optimized Elliptic Envelope Models

(2021) Yongliang Chen et al.   Journal of Earth Science

Geochemically Constrained Prospectivity Mapping Aided by Unsupervised Cluster Analysis

(2021) Shuai Zhang et al.   Natural Resources Research

The processing methods of geochemical exploration data: past, present, and future

(2021) Renguang Zuo et al.   APPLIED GEOCHEMISTRY

Mineral exploration targeting by combination of recursive indicator elimination with the ℓ2-regularization logistic regression based on geochemical data

(2021) Yongliang Chen et al.   ORE GEOLOGY REVIEWS

Visualization and interpretation of geochemical exploration data using GIS and machine learning methods

(2021) Renguang Zuo et al.   APPLIED GEOCHEMISTRY

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

(2021) Yun-Zhao Ge et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

Application of self-organizing map (SOM) and K-means clustering algorithms for portraying geochemical anomaly patterns in Moalleman district, NE Iran

(2021) Amirreza Bigdeli et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

Effects of Random Negative Training Samples on Mineral Prospectivity Mapping

(2020) Renguang Zuo et al.   Natural Resources Research

Identification of multi-element geochemical anomalies using unsupervised machine learning algorithms: A case study from Ag–Pb–Zn deposits in north-western Zhejiang, China

(2020) Jun Wang et al.   APPLIED GEOCHEMISTRY

Modeling of Cu-Au prospectivity in the Carajás mineral province (Brazil) through machine learning: Dealing with imbalanced training data

(2020) Elias Martins Guerra Prado et al.   ORE GEOLOGY REVIEWS

Using geostatistics and maximum entropy model to identify geochemical anomalies: A case study in Mila Mountain region, southern Tibet

(2020) Binbin Li et al.   APPLIED GEOCHEMISTRY

Mapping Geochemical Anomalies Through Integrating Random Forest and Metric Learning Methods

(2019) Ziye Wang et al.   Natural Resources Research

Compositional Balance Analysis: An Elegant Method of Geochemical Pattern Recognition and Anomaly Mapping for Mineral Exploration

(2019) Yue Liu et al.   Natural Resources Research

Mapping of single- and multi-element geochemical indicators based on catchment basin analysis: Application of fractal method and unsupervised clustering models

(2019) Reza Ghezelbash et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

Applying spatial prospectivity mapping to exploration targeting: Fundamental practical issues and suggested solutions for the future

(2019) Jon M.A. Hronsky et al.   ORE GEOLOGY REVIEWS

State-of-the-art analysis of geochemical data for mineral exploration

(2019) E. C. Grunsky et al.   GEOCHEMISTRY-EXPLORATION ENVIRONMENT ANALYSIS

A knowledge-driven way to interpret the isometric log-ratio transformation and mixture distributions of geochemical data

(2019) Xiangchong Liu et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

Practical Implementation of Random Forest-Based Mineral Potential Mapping for Porphyry Cu–Au Mineralization in the Eastern Lachlan Orogen, NSW, Australia

(2019) Arianne Ford   Natural Resources Research

GIS-based rare events logistic regression for mineral prospectivity mapping

(2018) Yihui Xiong et al.   COMPUTERS & GEOSCIENCES

Compositional balance analysis for geochemical pattern recognition and anomaly mapping in the western Junggar region, China

(2018) Yue Liu et al.   GEOCHEMISTRY-EXPLORATION ENVIRONMENT ANALYSIS

Selection of an elemental association related to mineralization using spatial analysis

(2018) Renguang Zuo   JOURNAL OF GEOCHEMICAL EXPLORATION

Maximum Entropy and Random Forest Modeling of Mineral Potential: Analysis of Gold Prospectivity in the Hezuo–Meiwu District, West Qinling Orogen, China

(2018) Shuai Zhang et al.   Natural Resources Research

Union score and fuzzy logic mineral prospectivity mapping using discretized and continuous spatial evidence values

(2017) Mahyar Yousefi et al.   JOURNAL OF AFRICAN EARTH SCIENCES

A new method for correlation analysis of compositional (environmental) data – a worked example

(2017) C. Reimann et al.   SCIENCE OF THE TOTAL ENVIRONMENT

A Receiver Operating Characteristics-Based Geochemical Data Fusion Technique for Targeting Undiscovered Mineral Deposits

(2017) Mohammad Parsa et al.   Natural Resources Research

Random Forest-Based Prospectivity Modelling of Greenfield Terrains Using Sparse Deposit Data: An Example from the Tanami Region, Western Australia

(2017) Siddharth Hariharan et al.   Natural Resources Research

Machine Learning of Mineralization-Related Geochemical Anomalies: A Review of Potential Methods

(2017) Renguang Zuo   Natural Resources Research

Application of ant colony algorithm to geochemical anomaly detection

(2016) Yongliang Chen et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

Recognition of significant multi-element geochemical signatures of porphyry Cu deposits in Noghdouz area, NW Iran

(2016) Mohammad Parsa et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

Data-driven logistic-based weighting of geochemical and geological evidence layers in mineral prospectivity mapping

(2016) Mahyar Yousefi et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

Prediction–area (P–A) plot and C–A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling

(2015) Mahyar Yousefi et al.   COMPUTERS & GEOSCIENCES

Random forest predictive modeling of mineral prospectivity with small number of prospects and data with missing values in Abra (Philippines)

(2015) Emmanuel John M. Carranza et al.   COMPUTERS & GEOSCIENCES

Origin of the ore-forming fluids and metals of the Bangpu porphyry Mo–Cu deposit of Tibet, China: Constraints from He–Ar, H–O, S and Pb isotopes

(2015) Liqiang Wang et al.   JOURNAL OF ASIAN EARTH SCIENCES

Supervised geochemical anomaly detection by pattern recognition

(2015) Arman Mohammadi Gonbadi et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

On the purity of training and testing data for learning: The case of pedestrian detection

(2015) Matteo Taiana et al.   NEUROCOMPUTING

Receiver operating characteristics (ROC) as validation tool for prospectivity models — A magmatic Ni–Cu case study from the Central Lapland Greenstone Belt, Northern Finland

(2015) Vesa Nykänen et al.   ORE GEOLOGY REVIEWS

Machine learning predictive models for mineral prospectivity: An evaluation of neural networks, random forest, regression trees and support vector machines

(2015) V. Rodriguez-Galiano et al.   ORE GEOLOGY REVIEWS

Application of Discriminant Analysis and Support Vector Machine in Mapping Gold Potential Areas for Further Drilling in the Sari-Gunay Gold Deposit, NW Iran

(2015) Hamid Geranian et al.   Natural Resources Research

Predictive modelling of gold potential with the integration of multisource information based on random forest: a case study on the Rodalquilar area, Southern Spain

(2014) V.F. Rodriguez-Galiano et al.   INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE

A study of the lake sediment geochemistry of the Melville Peninsula using multivariate methods: Applications for predictive geological mapping

(2013) E.C. Grunsky et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

Contribution of mantle components within juvenile lower-crust to collisional zone porphyry Cu systems in Tibet

(2012) Zengqian Hou et al.   MINERALIUM DEPOSITA

Isolation-Based Anomaly Detection

(2012) Fei Tony Liu et al.   ACM Transactions on Knowledge Discovery from Data

Interpretation of multivariate outliers for compositional data

(2011) Peter Filzmoser et al.   COMPUTERS & GEOSCIENCES

An assessment of the effectiveness of a random forest classifier for land-cover classification

(2011) V.F. Rodriguez-Galiano et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Support vector machine: A tool for mapping mineral prospectivity

(2010) Renguang Zuo et al.   COMPUTERS & GEOSCIENCES

Receiver Operating Characteristic Curve in Diagnostic Test Assessment

(2010) Jayawant N. Mandrekar   Journal of Thoracic Oncology

Objective selection of suitable unit cell size in data-driven modeling of mineral prospectivity

(2009) Emmanuel John M. Carranza   COMPUTERS & GEOSCIENCES

Application of singularity mapping technique to identify local anomalies using stream sediment geochemical data, a case study from Gangdese, Tibet, western China

(2008) Renguang Zuo et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

The Miocene Gangdese porphyry copper belt generated during post-collisional extension in the Tibetan Orogen

(2008) Zengqian Hou et al.   ORE GEOLOGY REVIEWS

Radial Basis Functional Link Nets Used as a Prospectivity Mapping Tool for Orogenic Gold Deposits Within the Central Lapland Greenstone Belt, Northern Fennoscandian Shield

(2008) Vesa Nykänen   Natural Resources Research

Selection of coherent deposit-type locations and their application in data-driven mineral prospectivity mapping

(2007) E.J.M. Carranza et al.   ORE GEOLOGY REVIEWS