IEEE Systems, Man and Cybernetics Magazine - January 2023 - 23

Number
MAPE
RMSE
Number
MAPE
RMSE
Table 1. A prediction result based on the DPNN.
2
1
0.082
0.0675
11
0.0846
0.0688
0.0785
0.0632
12
0.0878
0.07
3
0.0774
0.0658
13
0.0876
0.0704
4
0.0812
0.0667
14
0.0846
0.0688
5
0.0876
0.0704
15
0.0823
0.0665
6
0.0823
0.0665
16
0.0878
0.07
7
0.0867
0.0703
17
0.0843
0.0683
8
0.0843
0.0683
18
0.0876
0.0704
9
0.0812
0.0664
19
0.0846
0.0688
10
0.0878
0.0709
20
0.0867
0.0703
Number
MAPE
RMSE
Number
MAPE
RMSE
Table 2. A prediction result based on the LS-SVM.
2
1
0.1568
0.0973
11
0.1367
0.0984
0.1367
0.0984
12
0.0992
0.0825
3
0.2139
0.1408
13
0.1127
0.0871
4
0.1127
0.0871
14
0.1141
0.0911
5
0.1559
0.128
15
0.1559
0.128
6
0.1551
0.1708
16
0.1536
0.1062
7
0.1536
0.1062
17
0.1261
0.1221
8
0.2049
0.1382
18
0.1611
0.1026
9
0.1261
0.1221
19
0.2310
0.1185
10
0.1611
0.1026
20
0.1196
0.0974
Number
MAPE
RMSE
CC
Number
MAPE
RMSE
CC
Table 3. A prediction result based on LSTM.
2
1
0.1933
0.1101
0.9252
11
0.1673
0.1408
0.6659
0.1709
0.1099
0.896
12
0.2191
0.1243
0.8477
3
0.1876
0.1106
0.9154
13
0.2125
0.1235
0.8742
4
0.2142
0.143
0.7895
14
0.1368
0.0995
0.8821
5
0.2111
0.1238
0.8415
15
0.1822
0.1428
0.6706
6
0.1658
0.1153
0.8361
16
0.1742
0.1112
0.9132
7
0.185
0.1197
0.848
17
0.2015
0.1395
0.7209
8
0.2156
0.1234
0.9111
18
0.1889
0.1241
0.8423
9
0.2123
0.1313
0.9452
19
0.1891
0.1176
0.8745
10
0.2102
0.1405
0.8313
20
0.2116
0.1057
0.8923
1.1
0.9
1
0.8
0.6
0.7
0.5
0.4
0.3
0.2
0.1
Actual Value
LS-SVM
LSTM
DPNN
0 100 200 300 400 500 600 700 800 900
Time Step
Figure 6. A comparison of prediction results of the
DPNN with the LS-SVM and LSTM.
the corresponding author. This article has supplementary
downloadable material available at https://doi.org/10.1109/
MSMC.2022.3218424, provided by the authors.
About the Authors
Sheng Hong (shenghong@buaa.edu.cn) is a professor at
Nanchang University, Nanchang. JiangXi 330031, China, a
doctoral supervisor at Beihang University, an academic leader
of safety in Beijing, a technical expert with the Beijing
Municipal Science and Technology Commission, and an
Excellent Young Talent at Beihang University, Beijing 100191,
China. He is engaged in the teaching and scientific research
of network information, the industrial Internet, and the general
quality characteristics technology of complex systems, and
he has presided over and participated in the National Basic
Research Program of China, National Key Research and
January 2023 IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE 23
RUL

https://doi.org/10.1109/MSMC.2022.3218424 https://doi.org/10.1109/MSMC.2022.3218424

IEEE Systems, Man and Cybernetics Magazine - January 2023

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