Application of Discriminant Analysis and Support Vector Machine in Mapping Gold Potential Areas for Further Drilling in the Sari-Gunay Gold Deposit, NW Iran-Reference-Cited by-同舟云学术

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

Published:2015-06-12 Issue:2 Volume:25 Page:145-159
ISSN:1520-7439
Container-title:Natural Resources Research
language:en
Short-container-title:Nat Resour Res

Author:

Geranian Hamid,Tabatabaei Seyed Hassan,Asadi Hooshang H.,Carranza Emmanuel John M.

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science

Link

http://link.springer.com/content/pdf/10.1007/s11053-015-9271-2.pdf

Reference79 articles.

1. Abbaszadeh, M., Hezarkhani, A., & Soltani-Mohammad, S. (2013). An SVM-based machine learning method for the separation of alteration zones in Sungun porphyry copper deposit. Chemie der Erde: Geochemistry, 73, 545–554

2. Abedi, M., Norouzi, G. H., & Bahroudi, A. (2012). Support vector machine for multi-classification of mineral prospectivity areas. Computers & Geosciences, 46, 272–283

3. Agterberg, F. P. (1974). Automatic contouring of geological maps to detect areas for mineral exploration. Mathematical Geology, 6, 373–395

4. Al-Anazi, A., & Gates, I. D. (2010). On the capability of support vector machines to classify lithology from well logs. Natural Resources Research, 19, 125–139

5. Alavi, M. (1994). Tectonics of Zagros Orogenic belt of Iran, new data and interpretation. Tectonophysics, 229, 211–238

Cited by 63 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predictive modelling of mineral prospectivity using satellite remote sensing and machine learning algorithms;Remote Sensing Applications: Society and Environment;2024-11

2. Adopting a cell-based method to identify mineralized geological structures in support of mineral prospectivity mapping at the Kuh–Lakht epithermal gold deposit, Central Iran;Ore Geology Reviews;2024-08

3. A Spectral and Spatial Comparison of Satellite-Based Hyperspectral Data for Geological Mapping;Remote Sensing;2024-06-09

4. A Comparative Analysis of Artificial Neural Network (ANN) and Gene Expression Programming (GEP) Datadriven Models for Prospecting Porphyry Cu Mineralization; Case Study of Shahr-e- Babak Area, Kerman Province, SE Iran;J MIN ENVIRON;2024

5. Predictive Mapping of Prospectivity for Gold in the Central Portion of the Tapajós Mineral Province, Brazil;Minerals;2023-11-12