fuhe.m

粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation)

function [p , q ] = fuhe
%  shuju wenjian 

p = [
     6.9966   10.4442   6.60   6.80   15.5   6.90   12.8   6.50   2.7
     5.9826   9.22740   5.80   5.90   13.9   6.00   11.8   5.40   2.5
     5.1714   8.61900   5.20   5.30   13.5   5.50   10.4   4.80   2.3
     4.8165   7.60500   4.80   4.80   11.3   5.10   10.1   4.10   1.7
     4.5630   7.19940   4.60   4.70   12.5   4.70   9.60   4.00   1.6
     4.4616   7.09800   4.40   4.40   11.2   4.80   9.30   3.90   1.7
     4.4616   6.84450   4.10   4.80   10.1   5.10   9.90   4.20   1.8
     4.8672   7.50360   4.10   5.60   12.3   6.70   12.1   5.00   2.4
     5.8812   9.37950   4.50   7.70   13.6   12.2   17.2   6.90   4.7
     7.3008   13.0299   8.30   11.0   15.7   15.5   22.4   8.80   5.6
     8.1016   13.7904   8.50   11.7   16.5   16.5   25.1   10.1   5.9
     9.0753   14.5509   9.10   11.9   17.8   17.4   25.8   10.6   6.6
     9.6837   15.5649   9.50   10.4   18.6   18.4   27.5   11.4   6.8
     9.5832   14.9058   8.90   10.1   19.8   17.3   25.6   10.9   6.2
     8.7711   14.3481   8.70   10.1   18.8   16.6   24.9   10.5   6.2  
     8.3655   14.2467   9.10   10.4   17.6   16.9   25.8   10.5   6.2
     8.5683   14.0946   8.90   10.9   18.4   16.7   25.4   10.6   5.8
     9.1260   13.9425   8.50   10.2   18.4   16.0   25.3   10.5   5.7
     9.5823   14.2467   9.20   9.90   19.4   12.7   23.7   9.60   4.3
     9.6837   13.7904   10.0   10.0   19.7   11.9   20.8   8.60   3.8
     9.7344   13.7904   9.60   9.80   19.4   11.3   18.8   8.50   3.7
     9.4809   13.5876   9.90   9.60   19.4   10.7   18.1   8.50   3.5
     9.1767   13.4862   9.80   9.50   18.9   9.50   16.6   8.00   2.9
     8.3148   12.5736   8.40   8.80   19.7   8.20   15.4   7.50   2.7 ]; 
 
 q = [
     4.0107   5.0754   3.0   2.6   8.00   3.2   5.80   3.200   1.100
     3.8079   4.5684   2.8   2.3   7.70   2.9   5.50   2.800   0.900
     1.7745   4.4163   2.6   2.0   7.80   2.6   4.60   2.500   0.900
     1.6731   4.0107   2.6   2.0   6.20   2.5   4.60   2.400   0.600
     1.5717   3.8586   2.5   2.0   6.90   2.3   4.30   2.200   0.500
     1.6224   3.8079   2.3   2.0   6.30   2.4   4.20   2.300   0.600
     1.7238   3.7572   2.3   2.0   5.90   2.6   4.50   2.300   0.700
     2.0787   4.7712   2.3   2.4   7.20   3.6   5.60   2.800   1.000
     4.2642   5.8359   3.0   4.1   8.50   6.2   10.2   4.316   2.516
     5.0247   7.5597   4.2   4.9   9.70   7.9   13.1   5.416   3.016
     5.2275   7.8132   4.3   5.5   10.0   8.4   14.1   6.016   3.216
     5.4303   8.0667   4.5   5.2   10.6   8.6   14.5   6.216   3.616
     5.3289   8.3709   4.8   5.0   11.3   9.7   15.9   6.716   3.816
     5.4810   8.0160   4.4   4.6   11.7   8.7   14.4   6.316   3.216
     5.0754   7.8132   4.2   4.7   11.0   7.9   13.7   5.816   3.216
     5.0768   7.7118   4.5   5.0   10.5   8.3   14.4   5.916   3.316
     5.0768   7.6611   4.3   5.3   10.9   8.3   14.2   5.916   3.116
     5.3796   7.7625   4.3   5.1   11.1   8.0   14.4   5.616   3.116
     5.1768   7.5090   5.2   5.3   12.0   6.0   14.7   5.616   2.416
     5.4303   7.3569   5.3   4.9   11.1   5.3   12.3   4.616   2.016
     5.4303   7.3569   5.3   4.8   11.1   5.1   11.3   4.616   2.016
     5.2782   7.1034   5.4   4.8   10.7   4.7   11.1   4.816   2.016
     4.6698   6.5964   4.6   3.8   9.50   3.7   7.80   4.116   1.116
     4.2642   6.0387   3.8   3.4   9.60   3.7   7.00   3.600   0.900 ];