Volume 33 Issue 10
Jul.  2021
Turn off MathJax
Article Contents
Abstract
Related Articles
NIU Jing-kao. Prediction of demand for iron ores in China based on principal component regression analysis[J]. Chinese Journal of Engineering, 2011, 33(10): 1177-1181. DOI: 10.13374/j.issn1001-053x.2011.10.019
Citation: NIU Jing-kao. Prediction of demand for iron ores in China based on principal component regression analysis[J]. Chinese Journal of Engineering, 2011, 33(10): 1177-1181. DOI: 10.13374/j.issn1001-053x.2011.10.019
shu

Prediction of demand for iron ores in China based on principal component regression analysis

  • 1. School of Civil and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China;

  • 2. Development Center for Metallurgical Science & Technology, China Association of Iron & Steel Industry, Beijing 100711, China

More Information
  • Received Date: October 07, 2010
  • Available Online: July 29, 2021
    Graphical Abstract
    • Abstract
  • Based on predicted methods of demand for iron ores,eight basic factors influencing the demand for iron ores in China were selected for single factor regressing analysis.The results show that the degree of correlation between the eight basic factors and demand for iron ores is more than 0.9.The principal component analysis method was used to analyze the relationships among the eight basic factors and four principal components were determined among the eight basic factors.Combined the principal component analysis method with the regressing analysis method,a prediction model of demand for iron ores was established.Using the model,the demands for iron ores in 2015 and 2020 in China were predicted and their values are 29.76 billion tons and 26.68 billion tons,respectively.
    • FullText(HTML)
    • References (0)
    • Related Articles

  • Related Articles

    [1]YAN Bing-qian, REN Fen-hua, CAI Mei-feng, GUO Qi-feng, WANG Pei-tao. Application of PCA and Bayesian MCMC to discriminate between water sources in seabed gold mines[J]. Chinese Journal of Engineering, 2019, 41(11): 1412-1421. DOI: 10.13374/j.issn2095-9389.2019.06.03.004
    [2]WANG Wei, HUANG Yu-xing, YU Hong-min. Data mining of deep drawing simulation results based on CART decision tree theory[J]. Chinese Journal of Engineering, 2018, 40(11): 1373-1379. DOI: 10.13374/j.issn2095-9389.2018.11.011
    [3]HE Fei, XU Jin-wu, YANG Jian-hong, LI Min. Cause analysis of the head width narrowing of hot rolled strips based on the kernel principal component analysis[J]. Chinese Journal of Engineering, 2012, 34(4): 437-443. DOI: 10.13374/j.issn1001-053x.2012.04.008
    [4]LIN Lu, BAO Yan-ping, YUE Feng, WANG Min, OU Hong-lin. RH decarburization model based on off-gas analysis[J]. Chinese Journal of Engineering, 2011, 33(S1): 20-24. DOI: 10.13374/j.issn1001-053x.2011.s1.010
    [5]YANG Shangyu, WANG Xudong, YAO Man, LI Quanyu. Application of improved principal component analysis method to mould process monitoring in continuous casting[J]. Chinese Journal of Engineering, 2008, 30(1): 80-83. DOI: 10.13374/j.issn1001-053x.2008.01.010
    [6]YUAN Li, MU Zhichun, LIU Leiming. Ear recognition based on kernel principal component analysis and support vector machine[J]. Chinese Journal of Engineering, 2006, 28(9): 890-895. DOI: 10.13374/j.issn1001-053x.2006.09.019
    [7]GUO Hui, WANG Ling, LIU Heping. Integrating kernel principal component analysis with least squares support vector machines for time series forecasting problems[J]. Chinese Journal of Engineering, 2006, 28(3): 303-306. DOI: 10.13374/j.issn1001-053x.2006.03.022
    [8]XU Zhengguang, WANG Shusheng, LIU Jiwei, WANG Zhiliang, SHI Lifeng. Application of kernel Fisher method based on primary factor analysis to recognition problem between oil layer and water layer[J]. Chinese Journal of Engineering, 2005, 27(1): 126-128. DOI: 10.13374/j.issn1001-053x.2005.01.032
    [9]WEN Hu, XU Jingcai. Dynamic Mathematical Model and Numerical Analysis of Coal Spontaneous Combustion Process[J]. Chinese Journal of Engineering, 2003, 25(5): 387-390. DOI: 10.13374/j.issn1001-053x.2003.05.027
    [10]Liu Yongcai, Cheng Huojin, Song Liantian, Shi Zhiru. Mathematic Model for Percussive Rock Drilling and Its Application to the Piston Failure Analysis[J]. Chinese Journal of Engineering, 1995, 17(4): 320-324. DOI: 10.13374/j.issn1001-053x.1995.04.003

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (333) PDF downloads (22) Cited by()
    Related

    Editorial Office of Chinese Journal of Engineering

    Address：No. 30 College Road, Haidian District, BeijingPost Code：100083 Tel：(010)62333436

    Supported by: Beijing Renhe Information Technology Co., Ltd.    Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return