Journal of Systems Engineering and Electronics ›› 2018, Vol. 29 ›› Issue (3): 560570.doi: 10.21629/JSEE.2018.03.13
• Systems Engineering • Previous Articles Next Articles
Kedong YIN^{1,}^{2}(), Yan GENG^{1}(), Xuemei LI^{1,}^{2,}*()
Received:
20170406
Online:
20180628
Published:
20180702
Contact:
Xuemei LI
Email:yinkedong@126.com;gengyan758@126.com;lixuemei@ouc.edu.cn
About author:
YIN Kedong was born in 1965. He received his B.E. degree from Nanjing University of Science and Technology in 1988 and M.Ec. degree from Ocean University of China. He is currently a professor, and a D.B.A. supervisor at Ocean University of China. His research interests include quantitative economic analysis and modeling, risk management and control, marine disaster assessment, marine resources and environmental management. Email: Supported by:
Kedong YIN, Yan GENG, Xuemei LI. Improved grey prediction model based on exponential grey action quantity[J]. Journal of Systems Engineering and Electronics, 2018, 29(3): 560570.
Table 1
Comparison of three models for the exponential change sequences"
Sequence   GM(1, 1)/%  LGM(1, 1)/%  EOGM(1, 1)/% 
 0.1  0.105 2  0.119 6  0.115 1 
0.2  0.498 3  0.493 2  0.362 1  
0.4  2.613 4  2.614 0  0.810 0  
0.6  8.182 8  5.493 9  1.364 8  
 1.0  23.543 7  23.547 2  1.955 1 
Table 2
Comparison of three models for the linear oscillation sequences with fixed trend"
Sequence  GM(1, 1)/%  LGM(1, 1)/%  EOGM(1, 1)/%  
 0.5  8.836 9  8.484 1  14.293 9 
1  7.563 9  8.575 2  5.268 9  
2  8.556 0  8.389 8  10.630 7  
4  10.028 0  15.588 4  13.116 6  
10  9.926 4  9.762 2  15.952 5 
Table 3
Comparison of three models for the sequences of exponential oscillation"
Sequence   GM(1, 1)/%  LGM(1, 1)/%  EOGM(1, 1)/% 
 0.1  4.297 6  5.521 5  3.469 3 
0.2  10.579 8  13.102 6  7.394 1  
0.4  3.952 7  7.874 9  2.378 6  
0.6  14.498 3  13.610 8  9.959 2  
 1.0  29.909 4  34.977 6  4.320 1 
Table 4
Comparison of three models for simulated predictive value and RPE"
Number  Actual value  GM(1, 1) predictive value  LGM(1, 1) predictive value  EOGM(1, 1) predictive value  GM(1, 1) RPE/%  LGM(1, 1) RPE/%  EOGM(1, 1) RPE/% 
1  100  100  100  100  0  0  0 
2  97.024 9  97.067 2  97.264 9  97.016 7  0.043 6  0.247 4  0.008 5 
3  95.084 1  95.090 4  95.320 5  95.079 6  0.006 6  0.248 6  0.004 7 
4  93.172 4  93.153 9  93.405 2  93.166 8  0.019 9  0.249 9  0.006 0 
5  91.289 3  91.256 8  91.518 7  91.284 0  0.035 6  0.251 3  0.005 8 
6  89.434 5  89.398 4  89.660 5  89.430 1  0.040 4  0.252 7  0.004 9 
7  87.607 5  87.577 8  87.830 2  87.601 9  0.033 9  0.254 2  0.006 4 
8  85.808 1  85.794 3  86.027 4  85.802 9  0.016 1  0.255 6  0.006 1 
Table 5
Comparison of predictive values and RPEs of the three models"
Number  Actual value  GM(1, 1) predictive value  LGM(1, 1) predictive value  EOGM(1, 1) predictive value  GM(1, 1) RPE/%  LGM(1, 1) RPE/%  EOGM(1, 1) RPE/% 
9  84.026 9  84.047 1  84.251 6  84.025 8  0.024 0  0.267 4  0.001 3 
10  82.282 5  82.335 5  82.502 5  82.280 5  0.064 4  0.267 4  0.002 4 
Table 7
Comparison of simulated values and relative percentage of tertiary industry in three model"
Year  Actualvalue  GM(1, 1)predictive value  LGM(1, 1)predictive value  EOGM(1, 1)predictive value  GM(1, 1)RPE/%  LGM(1, 1)RPE/%  EOGM(1, 1)RPE/% 
2005  1 590.7  1 590.7  1 590.7  1 590.7  0  0  0 
2006  1 815.3  1 896.7  1 717.4  1 847.3  4.451 1  5.393 0  1.762 8 
2007  2 106.7  2 084.3  1 958.7  2 077.8  1.063 3  7.025 2  1.371 8 
2008  2 327.1  2 291.1  2 201.0  2 302.6  1.547 0  5.418 8  1.052 8 
2009  2 547.4  2 518.5  2 444.2  2 536.2  1.134 5  4.051 2  0.439 7 
2010  2 794.1  2 768.5  2 688.3  2 786.9  0.916 2  3.786 6  0.257 7 
2011  3 059.7  3 043.2  2 933.5  3 056.4  0.539 3  4.124 6  0.107 9 
2012  3 303.3  3 345.3  3 179.6  3 333.8  1.271 5  3.744 7  0.923 3 
Table 8
Forecast values and RPEs of GDP index of tertiary industry in 2013 – 2014 "
Year  Actualvalue  GM(1, 1)predictive value  LGM(1, 1)predictive value  EOGM(1, 1)predictive value  GM(1, 1)RPE/%  LGM(1, 1)RPE/%  EOGM(1, 1)RPE/% 
2013  3 576.0  3 677.3  3 426.8  3 650.3  2.832 8  4.172 3  2.077 7 
2014  3 856.6  4 042.3  3 674.9  3 987.4  4.815 1  4.711 4  3.391 6 
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