Research Article

Dynamic Multi-Swarm Differential Learning Quantum Bird Swarm Algorithm and Its Application in Random Forest Classification Model

Table 4

Comparison on nine unimodal functions with 5 hybrid algorithms (Dim = 10).

FunctionTermBSADEDMSDL-PSODMSDL-BSADMSDL-QBSA

Max1.0317E + 041.2466E + 041.7232E + 041.0874E + 047.4436E + 01
Min04.0214E + 031.6580E − 0200
Mean6.6202E + 004.6622E + 036.0643E + 016.3444E + 003.3920E − 02
Var2.0892E + 028.2293E + 027.3868E + 021.9784E + 021.2343E + 00

Max3.3278E + 021.8153E + 028.0436E+014.9554E+022.9845E + 01
Min4.9286E − 1821.5889E + 011.0536E − 013.0074E − 1820
Mean5.7340E − 021.8349E + 012.9779E + 006.9700E − 021.1220E − 02
Var3.5768E + 004.8296E + 002.4966E + 005.1243E + 004.2864E − 01

Max1.3078E + 041.3949E + 041.9382E + 041.2899E + 048.4935E + 01
Min3.4873E − 2504.0327E + 036.5860E − 021.6352E − 2490
Mean7.6735E + 004.6130E + 038.6149E + 017.5623E + 003.3260E − 02
Var2.4929E + 028.4876E + 028.1698E + 022.4169E + 021.2827E + 00

Max2.5311E + 092.3900E + 094.8639E + 093.7041E + 093.5739E + 08
Min5.2310E + 002.7690E + 088.4802E + 005.0021E + 008.9799E + 00
Mean6.9192E + 053.3334E + 081.1841E + 079.9162E + 056.8518E + 04
Var3.6005E + 071.4428E + 081.8149E + 084.5261E + 074.0563E + 06

Max1.1619E + 041.3773E + 041.6188E + 041.3194E + 045.1960E + 03
Min5.5043E − 155.6109E + 031.1894E − 024.2090E − 151.5157E + 00
Mean5.9547E + 006.3278E + 035.2064E + 016.5198E + 003.5440E + 00
Var2.0533E + 029.6605E + 026.2095E + 022.2457E + 027.8983E + 01

Max3.2456E + 007.3566E + 008.9320E + 002.8822E + 001.4244E + 00
Min1.3994E − 041.2186E + 002.2482E − 038.2911E − 051.0911E − 05
Mean2.1509E − 031.4021E + 001.1982E − 011.9200E − 036.1476E − 04
Var5.3780E − 023.8482E − 013.5554E − 015.0940E − 021.9880E − 02

Max4.7215E + 026.7534E + 025.6753E + 025.3090E + 022.3468E + 02
Min02.2001E + 025.6300E − 0200
Mean2.4908E − 012.3377E + 029.2909E + 003.0558E − 019.4500E − 02
Var8.5433E + 003.3856E + 012.2424E + 011.0089E + 013.5569E + 00

Max3.2500E + 022.4690E + 022.7226E + 022.8001E + 021.7249E + 02
Min1.4678E − 2398.3483E + 015.9820E − 028.9624E − 2390
Mean1.9072E − 019.1050E + 017.9923E + 002.3232E − 018.1580E − 02
Var6.3211E + 001.3811E + 011.7349E + 016.4400E + 002.9531E + 00