• Volume 33 Issue 10
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    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

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

    doi: 10.13374/j.issn1001-053x.2011.10.019
    • Received Date: 2010-10-08
      Available Online: 2021-07-30
    • 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.

       

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