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
0.2875
0.2360
0.2044
0.1751
0.1316
0.0897
0.0167
0.0078
0.0836
0.1068
0.0530
0.0559
0.0140
0.0099
0.0847
0.1077
0.0542
0.0554
0.4804
0.4362
0.3407
0.2581
0.2073
0.1532
0.0164
0.0077
0.0834
0.1073
0.0534
0.0578
0.2781
0.2652
0.2740
0.2415
0.1498
0.1204
0.1250
0.1190
0.1033
0.0994
0.0969
0.0764
0.2886
0.3551
0.3512
0.3058
0.3123
0.3282
0.3258
0.3691
0.3580
0.3139
0.3113
0.3077
0.3631
0.4266
0.4234
0.3810
0.3659
0.3596
0.3655
0.4212
0.4163
0.3661
0.3657
0.3634
0.0849
0.0562
0.0951
0.0999
0.0470
0.0420
0.1386
0.0239
0.0194
0.0324
0.0238
0.0255
0.0166
0.0626
0.1350
0.1315
0.0403
0.0418
0.0126
0.1462
0.1520
0.1105
0.1133
0.1081
0.0196
0.0499
0.1233
0.1432
0.0867
0.0903
0.0223
0.0532
0.1281
0.1447
0.0886
0.0906
0.6827
0.5360
0.4059
0.2698
0.1854
0.1124
0.2578
0.2884
0.2852
0.2570
0.1989
0.1940
For the sake of convenience, first renumber the index after the gray relational model [46] optimization: “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”; “”.
