• 中国出版政府奖提名奖

    中国百强科技报刊

    湖北出版政府奖

    中国高校百佳科技期刊

    中国最美期刊

    Volume 34 Issue 2
    Mar.  2009
    Turn off MathJax
    Article Contents
    ZHANG Sheng-yuan, HUANG Rui, XU De-yi, CHENG Qiu-ming, 2009. Weighted Weights of Evidence and Stepwise Weights of Evidence and Their Applications in Sn-Cu Mineral Potential Mapping in Gejiu, Yunnan Province, China. Earth Science, 34(2): 347-352.
    Citation: ZHANG Sheng-yuan, HUANG Rui, XU De-yi, CHENG Qiu-ming, 2009. Weighted Weights of Evidence and Stepwise Weights of Evidence and Their Applications in Sn-Cu Mineral Potential Mapping in Gejiu, Yunnan Province, China. Earth Science, 34(2): 347-352.

    Weighted Weights of Evidence and Stepwise Weights of Evidence and Their Applications in Sn-Cu Mineral Potential Mapping in Gejiu, Yunnan Province, China

    • Received Date: 2009-01-16
    • Publish Date: 2009-03-25
    • This paper explores the possibility of applying non-negative matrix factorization (NMF) to process stream sediment geochemical data for mineral exploration. The brief introduction of principle of NMF is followed by detailed comparison of the results obtained by NMF and principal component analysis (PCA) applied to a dataset of 813 samples with six trace elements from Gejiu mineral district, Yunnan, China. It is shown that the NMF is not only suitable for processing geochemical data which are usually of positive values but also provides superior results than that by PCA in the case study introduced in the paper. The example indicates that NMF might become a useful method for processing other types of geochemical data.

       

    • loading
    • Cheng, Q. M., Zhao, P. D., Chen, J. G., et al., 2009. Application of singularity the oryin prediction of tin and coppermineral deposits in Gejiu district, Yunnan, China: Weak information extraction and mixing information decomposition. Earth Science—Journal of China University of Geosciences, 34 (2): 232-242 (in Chinese with Eng-lish abstract). doi: 10.3799/dqkxzx.2009.021
      Donoho, D., Stodden, V., 2004. When does non-negative matrix factorization give a correct decomposition into parts? In: Thrun, S., Saul, L., Scholkopf, B., eds., Advances in neural information processing systems16. MIT Press, Cambridge, MA.
      Feng, T., Li, S., Shum, H., et al., 2002. Local non-negative matrix factorization as a visual representation. In: Proceedings of the2ndinternational conference on development and learning. IEEE, Cambridge. U. K., 178-183. DOI: 10.1109/DEVLRN.2002.1011835.
      [40]
      Guillamet, D., Bressan, M., Vitria, J., 2001. A weighted non-negative matrix factorization for local representations. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition V1, Kauai, HI, 942-947. DOI: 10.1109/CVPR.2001.990629.
      Guillamet, D., Vitria, J., Schiele, B., 2003. Introducing a weighted non-negative matrix factorization for image classification. Pattern Recognition Letters, 24 (14): 2447-2454. doi: 10.1016/S0167-8655(03)00089-8
      Juvela, M., Lehtinen, K., Paatero, P., 1994. The use of positive matrix factorization in the analysis of molecular line spectra from the thumbprint nebula. In: Clemens, D. P., Barvainis, R., eds., Clouds, cores, and low mass star. ASP Conference Series, 65: 176-180.
      Juvela, M., Lehtinen, K., Paatero, P., 1996. The use of positive matrix factorization in the analysis of molecular linespectra. Mon. Not. R. Astron. Soc. , 280: 616-626. https://ui.adsabs.harvard.edu/abs/1996MNRAS.280..616J/abstract
      Lee, D. O., Seung, H. S., 1999. Learning the parts of objects by non-negative matrix factorization. Nature, 401: 788-791. doi: 10.1038/44565
      [50]
      Lee, D., Seung, H., 2000. Algorithms for non-negative matrix factorization. In: Leen, T., Dietterich, T., Tresp, V., eds., Advances in neural information processing systems. MIT Press, Cambridge, MA, 556-562.
      Paatero, P., 1997. Least squares formulation of robust non-negative factor analysis. Chemometrics and Intelligent Laboratory Systems, 37 (1): 23-35. doi: 10.1016/S0169-7439(96)00044-5
      Paatero, P., Tapper, U., 1994. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values. Environmetrics, 5 (2): 111-126. doi: 10.1002/env.3170050203
      Wei, L., 2004. Blind sources separation based on non-negative matrix factorization. Electronics Optics & Control, 11 (2): 38-41, 53 (in Chinese with English abstract).
      Xu, W., Liu, X., Gong, Y., 2003. Document-clustering based on non-negative matrix factorization. In: Proceedings ofSIGIR'03, July28-August1.267-273, Toronto, CA.
      成秋明, 赵鹏大, 陈建国, 等, 2009. 奇异性理论在个旧锡铜矿产资源预测中的应用: 成矿弱信息提取和复合信息分解. 地球科学——中国地质大学学报, 34 (2): 232-242. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX200902001.htm
      魏乐, 2004. 基于非负矩阵分解算法进行盲信号分离. 电光与控制, 11 (2): 38-41, 53. https://www.cnki.com.cn/Article/CJFDTOTAL-DGKQ200402011.htm
    • 加载中

    Catalog

      通讯作者: 陈斌, bchen63@163.com
      • 1. 

        沈阳化工大学材料科学与工程学院 沈阳 110142

      1. 本站搜索
      2. 百度学术搜索
      3. 万方数据库搜索
      4. CNKI搜索

      Figures(3)  / Tables(2)

      Article views (4031) PDF downloads(71) Cited by()
      Proportional views

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return