GIS-based rare events logistic regression for mineral prospectivity mapping
Tài liệu tham khảo
Abedi, 2012, Support vector machine for multi-classification of mineral prospectivity areas, Comput. Geosci., 46, 272, 10.1016/j.cageo.2011.12.014
Agterberg, 1999, Logistic regression and weights of evidence modeling in mineral exploration, 483
Allison, 2001
Batista, 2004, A study of the behavior of several methods for balancing machine learning training data, ACM Sigkdd Explor. Newsl., 6, 20, 10.1145/1007730.1007735
Brunsdon, 1996, Geographically weighted regression: a method for exploring spatial nonstationarity, Geogr. Anal., 28, 281, 10.1111/j.1538-4632.1996.tb00936.x
Carranza, 2001, Logistic regression for geologically constrained mapping of gold potential, Baguio district, Philippines, Explor. Min. Geol., 10, 165, 10.2113/0100165
Carranza, 2015, Data-driven predictive mapping of gold prospectivity, Baguio district, Philippines: application of random forests algorithm, Ore Geol. Rev., 71, 777, 10.1016/j.oregeorev.2014.08.010
Carranza, 2015, Random forest predictive modeling of mineral prospectivity with small number of prospects and data with missing values in Abra (Philippines), Comput. Geosci., 74, 60, 10.1016/j.cageo.2014.10.004
Carranza, 2016, Data-driven predictive modeling of mineral prospectivity using random forests: a case study in Catanduanes Island (Philippines), Nat. Resour. Res., 25, 35, 10.1007/s11053-015-9268-x
Chawla, 2003, 107
Chawla, 2004, Editorial: special issue on learning from imbalanced data sets, ACM Sigkdd Explor. Newsl., 6, 1, 10.1145/1007730.1007733
Cheng, 1996, Multifractal modeling and spatial statistics, Math. Geol., 28, 1, 10.1007/BF02273520
Cheng, 2000, Integrated spatial and spectrum method for geochemical anomaly separation, Nat. Resour. Res., 9, 43, 10.1023/A:1010109829861
Cheng, 2007, Mapping singularities with stream sediment geochemical data for prediction of undiscovered mineral deposits in Gejiu, Yunnan Province, China, Ore Geol. Rev., 32, 314, 10.1016/j.oregeorev.2006.10.002
Cox, 1989
Drummond, 2003, C4. 5, class imbalance, and cost sensitivity: why under-sampling beats over-sampling
Elkan, 2001, vol. 17, 973
Fabbri, 2008, On blind tests and spatial prediction models, Nat. Resour. Res., 17, 107, 10.1007/s11053-008-9072-y
Fawcett, 2006, An introduction to ROC analysis, Pattern Recognit. Lett., 27, 861, 10.1016/j.patrec.2005.10.010
Gao, 2016, Mapping mineral prospectivity for Cu polymetallic mineralization in southwest Fujian Province, China, Ore Geol. Rev., 75, 16, 10.1016/j.oregeorev.2015.12.005
Ge, 1981, Geological characteristics of the Makeng iron deposit of marine volcano-sedimentary origin, Acta Geosici. Sin., 3, 47
Granek, 2015, Data mining for real mining: a robust algorithm for prospectivity mapping with uncertainties, 145
Gribskov, 1996, Use of receiver operating characteristic (ROC) analysis to evaluate sequence matching, Comput. Chem., 20, 25, 10.1016/S0097-8485(96)80004-0
Guo, 2017, Learning from class-imbalanced data: review of methods and applications, Expert Syst. Appl., 73, 220, 10.1016/j.eswa.2016.12.035
Han, 1983, Geological and geochemical features of submarine volcanic hydrothermal-sedimentary mineralization of Makeng iron deposit, Fujian Province, Bull. Inst. Mineral Deposits Chin. Acad. Geol. Sci., 7, 1
Hariharan, 2017, Random forest-based prospectivity modelling of greenfield terrains using sparse deposit data: an example from the tanami region, western Australia, Nat. Resour. Res., 26, 489, 10.1007/s11053-017-9335-6
He, 2009, Learning from imbalanced data, IEEE Trans. Knowl. Data Eng., 21, 1263, 10.1109/TKDE.2008.239
Hosmer, 1989
Japkowicz, 2002, The class imbalance problem: a systematic study, Intell. data Anal., 6, 429, 10.3233/IDA-2002-6504
King, 2001, Logistic regression in rare events data, Polit. Anal., 9, 137, 10.1093/oxfordjournals.pan.a004868
Kubat, 1998, Machine learning for the detection of oil spills in satellite radar images, Mach. Learn., 30, 195, 10.1023/A:1007452223027
Leite, 2009, Probabilistic neural networks applied to mineral potential mapping for platinum group elements in the Serra Leste region, Carajás Mineral Province, Brazil, Comput. Geosci., 35, 675, 10.1016/j.cageo.2008.05.003
Li, 2013, Jurassic–Cretaceous tectonic evolution of Southeast China: geochronological and geochemical constraints of Yanshanian granitoids, Int. Geol. Rev., 55, 1202, 10.1080/00206814.2013.771952
Maloof, 2003, Learning when data sets are imbalanced and when costs are unequal and unknown
McKay, 2016, Comparison of the data-driven Random Forests model and a knowledge-driven method for mineral prospectivity mapping: a case study for gold deposits around the Huritz Group and Nueltin Suite, Nunavut, Canada, Nat. Resour. Res., 25, 125, 10.1007/s11053-015-9274-z
Menard, 2001
Metz, 1978, Basic principles of ROC analysis, Seminars Nucl. Med., 8, 283, 10.1016/S0001-2998(78)80014-2
Porwal, 2003, Artificial neural networks formineral potential mapping, Nat. Resour. Res., 12, 155, 10.1023/A:1025171803637
Porwal, 2006, Bayesian network classifiers for mineral potential mapping, Comput. Geosci., 32, 1, 10.1016/j.cageo.2005.03.018
Rodriguez-Galiano, 2014, Predictive modelling of gold potential with the integration of multisource information based on random forest: a case study on the Rodalquilar area, Southern Spain, Int. J. Geogr. Inf. Sci., 28, 1336, 10.1080/13658816.2014.885527
Seiffert, 2010, RUSBoost: a hybrid approach to alleviating class imbalance, IEEE Trans. Syst. Man, Cybernetics-Part A Syst. Humans, 40, 185, 10.1109/TSMCA.2009.2029559
Singer, 1996, Application of a feedforward neural network in the search for Kuruko deposits in the Hokuroku district, Japan, Math. Geol., 28, 1017, 10.1007/BF02068587
Shu, 2008, Late palaeozoic-early mesozoic geological features of south China: response to the indosinian collision events in southeast Asia, Comptes Rendus Geosci., 340, 151, 10.1016/j.crte.2007.10.010
Sun, 2007, The golden transformation of the Cretaceous plate subduction in the west Pacific, Earth Planet. Sci. Lett., 262, 533, 10.1016/j.epsl.2007.08.021
Sun, 2009, Classification of imbalanced data: a review, Int. J. Pattern Recognit. Artif. Intell., 23, 687, 10.1142/S0218001409007326
Tessema, 2017, Mineral systems analysis and artificial neural network modeling of chromite prospectivity in the western limb of the bushveld complex, South Africa, Nat. Resour. Res., 26, 465, 10.1007/s11053-017-9344-5
Trafalis, 2003, Tornado detection with support vector machines, Int. Conf. Comput. Sci., 289
Van Den Eeckhaut, 2006, Prediction of landslide susceptibility using rare events logistic regression: a case-study in the Flemish Ardennes (Belgium), Geomorphology, 76, 392, 10.1016/j.geomorph.2005.12.003
Wang, 2015, Spatial analysis of Fe deposits in Fujian province, China: implications for mineral exploration, J. Earth Sci., 26, 813, 10.1007/s12583-015-0597-9
Wang, 2015, Zircon U-Pb geochronology, geochemistry and Hf isotope compositions of the Dayang and Juzhou granites in Longyan, Fujian their Geol. Implic., 44, 450
Xiong, 2016, Recognition of geochemical anomalies using a deep autoencoder network, Comput. Geosci., 86, 75, 10.1016/j.cageo.2015.10.006
Xiong, 2017, Effects of misclassification costs on mapping mineral prospectivity, Ore Geol. Rev., 82, 1, 10.1016/j.oregeorev.2016.11.014
Xiong, 2017, Identification of geochemical anomalies via local RX anomaly detector, J. Geochem. Explor.
Yang, 2008, SHRIMP zircon U–Pb dating of quartz porphyry from Zhongjia tin–polymetallic deposit in Longyan area, Fujian Province, and its geological significance, Miner. Depos., 27, 329
Zhang, 2012, La-ICP-MS Zircon U-Pb ages and Hf isotopic compositions of dayang granite from longyan, Fujian province, Geoscience, 26, 434
Zhang, 2012, Geochronology of diagenesis and mineralization of the Luoyang iron deposit in Zhangping city, Fujian province and its geological significance. Earth Science, J. China Univ. Geosci., 37, 1217
Zhang, 2014, Sr–Nd–Pb isotope systematics of magnetite: implications for the genesis of Makeng Fe deposit, southern China, Ore Geol. Rev., 57, 53, 10.1016/j.oregeorev.2013.09.009
Zhang, 2015, The mineralization age of the Makeng Fe deposit, South China: implications from U-Pb and Sm-Nd geochronology, Int. J. Earth Sci., 104, 663, 10.1007/s00531-014-1096-4
Zhang, 2015, Geological features and formation processes of the Makeng Fe deposit, China, Resour. Geol., 65, 266, 10.1111/rge.12070
Zhang, 2016, A comparative study of fuzzy weights of evidence and random forests for mapping mineral prospectivity for skarn-type Fe deposits in the southwestern Fujian metallogenic belt, China, Sci. China Earth Sci., 59, 556, 10.1007/s11430-015-5178-3
Zhao, 2013, Investigation of spatially non-stationary influences of tectono-magmatic processes on Fe mineralization in eastern Tianshan, China with geographically weighted regression, J. Geochem. Explor., 134, 38, 10.1016/j.gexplo.2013.07.008
Zhou, 2000, Origin of Late Mesozoic igneous rocks in Southeastern China: implications for lithosphere subduction and underplating of mafic magmas, Tectonophysics, 326, 269, 10.1016/S0040-1951(00)00120-7
Zhou, 2006, Petrogenesis of Mesozoic granitoids and volcanic rocks in South China: a response to tectonic evolution, Episodes, 29, 26, 10.18814/epiiugs/2006/v29i1/004
Zhou, 2006, Training cost-sensitive neural networks with methods addressing the class imbalance problem, IEEE Trans. Knowl. Data Eng., 18, 63, 10.1109/TKDE.2006.17
Zuo, 2009, Application of singularity mapping technique to identification local anomalies using stream sediment geochemical data, a case study from Gangdese, Tibet, Western China, J. Geochem. Explor., 101, 225, 10.1016/j.gexplo.2008.08.003
Zuo, 2011, Identifying geochemical anomalies associated with Cu and Pb–Zn skarn mineralization using principal component analysis and spectrum–area fractal modeling in the Gangdese Belt, Tibet (China), J. Geochem. Explor., 111, 13, 10.1016/j.gexplo.2011.06.012
Zuo, 2011, Support vector machine: a tool for mapping mineral prospectivity, Comput. Geosci., 37, 1967, 10.1016/j.cageo.2010.09.014
Zuo, 2015, Evaluation of uncertainty in mineral prospectivity mapping due to missing evidence: a case study with skarn-type Fe deposits in Southwestern Fujian Province, China, Ore Geol. Rev., 71, 502, 10.1016/j.oregeorev.2014.09.024
Zuo, 2016, A nonlinear controlling function of geological features on magmatic–hydrothermal mineralization, Sci. Rep., 6, 27127, 10.1038/srep27127
Zuo, 2016, Spatial analysis and visualization of exploration geochemical data, Earth-Sci. Rev., 158, 9, 10.1016/j.earscirev.2016.04.006
Zuo, 2016, Fractal/multifractal modeling of geochemical data: a review, J. Geochem. Explor., 164, 33, 10.1016/j.gexplo.2015.04.010
Zuo, 2017, Machine learning of mineralization-related geochemical anomalies: a review of potential methods, Nat. Resour. Res., 26, 457, 10.1007/s11053-017-9345-4
Zuo, 2017, Selection of an elemental association related to mineralization using spatial analysis, J. Geochem. Explor.