Complexity / 2018 / Article / Tab 2

Research Article

Dynamic Prediction Research of Silicon Content in Hot Metal Driven by Big Data in Blast Furnace Smelting Process under Hadoop Cloud Platform

Table 2

Different time delay correlation coefficients under the input variables and the calculation results of the [Si]% list.

Input variable the previous hours

0.28750.23600.20440.17510.13160.0897
0.01670.00780.08360.10680.05300.0559
0.01400.00990.08470.10770.05420.0554
0.48040.43620.34070.25810.20730.1532
0.01640.00770.08340.10730.05340.0578
0.27810.26520.27400.24150.14980.1204
0.12500.11900.10330.09940.09690.0764
0.28860.35510.35120.30580.31230.3282
0.32580.36910.35800.31390.31130.3077
0.36310.42660.42340.38100.36590.3596
0.36550.42120.41630.36610.36570.3634
0.08490.05620.09510.09990.04700.0420
0.13860.02390.01940.03240.02380.0255
0.01660.06260.13500.13150.04030.0418
0.01260.14620.15200.11050.11330.1081
0.01960.04990.12330.14320.08670.0903
0.02230.05320.12810.14470.08860.0906
0.68270.53600.40590.26980.18540.1124
0.25780.28840.28520.25700.19890.1940

For the sake of convenience, first renumber the index after the gray relational model [46] optimization: “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”.

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