Journal of Systems Engineering and Electronics ›› 2023, Vol. 34 ›› Issue (5): 12351251.doi: 10.23919/JSEE.2023.000062
• Systems Engineering • Previous Articles Next Articles
Lei XIE^{1}(), Shangqin TANG^{1}(), Zhenglei WEI^{2}^{,}*(), Yongbo XUAN^{3}(), Xiaofei WANG^{3}()
Received:
20210224
Online:
20231018
Published:
20231030
Contact:
Zhenglei WEI
Email:310370487@qq.com;630909448@qq.com;zhenglei_wei@126.com;398791736@qq.com;wxf825421673@163.com
About author:
Supported by:
Lei XIE, Shangqin TANG, Zhenglei WEI, Yongbo XUAN, Xiaofei WANG. UCAV situation assessment method based on CLSHADEMeans and SAELVQ[J]. Journal of Systems Engineering and Electronics, 2023, 34(5): 12351251.
Table 1
Algorithm parameter settings"
Algorithm  Parameter setting 
LSHADE  H=3, MF=0.5, p_{init}=0.11, N_{init}=200, N_{min}=150, D=2 
CoBiDE  pb=0.4, ps=0.5, D=2 
DE  F=0.5, Cr=0.5, D=2 
SSA  Leader position update probability=0.5 
PSO  C_{1}=1.5, C_{2}=1.5, D=2, Inertia factor=0.3 
HHO  
GWO  a=2−2t/t_{max} 
GSA  α=20, G0=100, R_{norm}=2, R_{power}=1 
Table 2
Cluster evaluation index"
Index  Formula  Description 
Ac   
Sil   
DB   DB represents the proportion of cluster scatter between cluster separation. 
CH   
Table 3
Clustering algorithm parameter settings"
Number  Algorithm  Parameter setting 
1  DPC  Reference [ 
2  FCM  The index of the membership matrix is 2, the maximum number of iterations is 200, and the minimum membership is 1.0e−5 
3  GMM  The nonnegative regularization number is 1.0e−5 
4  CLA  Reference [ 
5  LGC  Reference [ 
6  Kmeans  Use Euclidean distance, the number of clusters is 4 
7  GBKMeans  Reference [ 
8  CLSHADEMeans  Use Euclidean distance, the number of clusters is 4, the maximum number of iterations is 200, CR=0.5,F=0.5, the initial population is 200, and the minimum population is 150 
Table 4
Clustering results"
Data  Index  DPC  FCM  GMM  CLA  GLA  Kmeans  CBKMeans  CLSHADEMeans 
UCI Data  Ac/%  63.24  74.57  80.35  84.1  84.2  75.43  77.43  86.86 
DB  0.6584  0.7850  0.7701  0.635  0.635  0.7627  0.750  0.7526  
CH  237.3047  339.5852  283.9508  336.248  336.249  340.2413  286.260  340.2610  
Sil  0.2468  0.4160  0.4084  0.402  0.410  0.4192  0.383  0.4348  
Rank  8/8  3/8  5/8  6/8  4/8  2/8  7/8  1/8 
Table 5
Network parameter settings"
Algorithm  Parameter setting 
HSVM  H=2, C=100, 
CSAHSVM  Fl=2.5, AP=0.1, iter=100, NP=20, C=100, 
KNN  K=4 
LVQ  
SAEHSVM  Number_AE=2,H=2, C=100, 
SAELVQ  Number_AE=2, 
Table 6
Comparison of performance indexes"
Classifier  Mean (SD)  
Accuracy/%  RMSE  MAPE/%  Kappa  Time  
HSVM  86.704(4.29e−01)  0.1208 (1.12e−02)  4.0262(4.61e−01)  0.7912 (6.4e−03)  9.183e−05 (1.862e−05) 
LVQ  94.663(2.81e−01)  0.0468 (4.3e−03)  2.6607(1.95e−01)  0.9113 (4.7e−03)  3.412e−05 (3.247e−06) 
CSASVM  94.10(7.43e−01)  0.062 (9.7e−03)  4.681(4.56e−01)  0.904 (1.20e−02)  3.16e−04 (7.34e−04) 
KNN  88.015(6.13e−01)  0.055 (1.27e−02)  6.99(7.43e−01)  0.804 (1.74e−02)  7.674e−05 (5.152e−05) 
SAe−HSVM  96.910(2.81e−01)  0.0356 (5.8e−03)  2.1223(5.49e−01)  0.9486 (4.6e−03)  4.435e−04 (6.882e−07) 
SAe−LVQ  99.251(1.62e−01)  0.0037 (1.6e−03)  0.5384(1.46e−01)  0.9876 (2.7e−3)  1.024e−04 (1.292e−05) 
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