| Fractal/multifractal modeling of geochemical data: A review R Zuo, J Wang Journal of Geochemical Exploration 164, 33-41, 2016 | 309 | 2016 |
| Deep learning and its application in geochemical mapping R Zuo, Y Xiong, J Wang, EJM Carranza Earth-science reviews 192, 1-14, 2019 | 263 | 2019 |
| Spatial analysis and visualization of exploration geochemical data R Zuo, EJM Carranza, J Wang Earth-Science Reviews 158, 9-18, 2016 | 145 | 2016 |
| Identification of weak anomalies: A multifractal perspective R Zuo, J Wang, G Chen, M Yang Journal of Geochemical Exploration 148, 12-24, 2015 | 133 | 2015 |
| The processing methods of geochemical exploration data: Past, present, and future R Zuo, J Wang, Y Xiong, Z Wang Applied Geochemistry 132, 105072, 2021 | 81 | 2021 |
| Mapping mineral prospectivity via semi-supervised random forest J Wang, R Zuo, Y Xiong Natural Resources Research 29, 189-202, 2020 | 78 | 2020 |
| Uncertainties in GIS-based mineral prospectivity mapping: Key types, potential impacts and possible solutions R Zuo, OP Kreuzer, J Wang, Y Xiong, Z Zhang, Z Wang Natural Resources Research 30, 3059-3079, 2021 | 68 | 2021 |
| Identification of geochemical anomalies through combined sequential Gaussian simulation and grid-based local singularity analysis J Wang, R Zuo Computers & Geosciences 118, 52-64, 2018 | 61 | 2018 |
| Discovering geochemical patterns by factor-based cluster analysis J Wang, R Zuo, J Caers Journal of Geochemical Exploration 181, 106-115, 2017 | 50 | 2017 |
| A MATLAB-based program for processing geochemical data using fractal/multifractal modeling J Wang, R Zuo Earth Science Informatics 8, 937-947, 2015 | 48 | 2015 |
| An extended local gap statistic for identifying geochemical anomalies J Wang, R Zuo Journal of Geochemical Exploration 164, 86-93, 2016 | 41 | 2016 |
| Recognizing geochemical anomalies via stochastic simulation-based local singularity analysis J Wang, R Zuo Journal of Geochemical Exploration 198, 29-40, 2019 | 37 | 2019 |
| Visualization and interpretation of geochemical exploration data using GIS and machine learning methods R Zuo, J Wang, B Yin Applied Geochemistry 134, 105111, 2021 | 32 | 2021 |
| Assessing geochemical anomalies using geographically weighted lasso J Wang, R Zuo Applied geochemistry 119, 104668, 2020 | 25 | 2020 |
| Identification of geochemical anomalies via local RX anomaly detector Y Xiong, R Zuo, K Wang, J Wang Journal of Geochemical Exploration 189, 64-71, 2018 | 25 | 2018 |
| Spatial modelling of hydrothermal mineralization-related geochemical patterns using INLA+ SPDE and local singularity analysis J Wang, R Zuo Computers & Geosciences 154, 104822, 2021 | 14 | 2021 |
| Geochemical anomaly identification and uncertainty quantification using a Bayesian convolutional neural network model D Huang, R Zuo, J Wang Applied Geochemistry 146, 105450, 2022 | 13 | 2022 |
| Model averaging for identification of geochemical anomalies linked to mineralization J Wang, R Zuo Ore Geology Reviews 146, 104955, 2022 | 13 | 2022 |
| A new generation of artificial intelligence algorithms for mineral prospectivity mapping R Zuo, Y Xiong, Z Wang, J Wang, OP Kreuzer Natural Resources Research 32 (5), 1859-1869, 2023 | 12 | 2023 |
| Quantifying the distribution characteristics of geochemical elements and identifying their associations in southwestern Fujian Province, China J Wang, R Zuo Minerals 10 (2), 183, 2020 | 11 | 2020 |
Renguang ZuoChina University of GeosciencesVerified email at cug.edu.cn
