改进的灰狼优化算法 GWO

代码说明：

  针对灰狼优化算法在求解连续函数优化问题时精度不高、易出现早熟收敛等缺陷,提出一种改进的灰狼优化算法(Grey Wolf Optimizer)

文件列表：

GWO
...\myself
...\......\GWO_finalVersion.pdf,1753133,2016-09-08
...\......\GWO_SVM_exmp.m,6625,2016-10-23
...\......\GWO_SVR_exmp.m,5780,2016-09-08
...\......\initialization.m,1845,2016-09-08
...\......\mymae.m,70,2016-09-08
...\......\mymape.m,85,2016-09-08
...\......\mymse.m,74,2016-09-08
...\......\wine.mat,20168,2016-09-08
...\......\wndspd.mat,447,2016-09-08
...\xuejies
...\.......\cec09.m,18039,2016-10-25
...\.......\CreateEmptyParticle.m,422,2016-10-25
...\.......\CreateHypercubes.m,529,2016-10-25
...\.......\DeleteFromRep.m,652,2016-10-25
...\.......\DetermineDomination.m,450,2016-10-25
...\.......\Dominates.m,172,2016-10-25
...\.......\GetCosts.m,107,2016-10-25
...\.......\GetGridIndex.m,3644,2015-12-15
...\.......\GetNonDominatedParticles.m,107,2016-10-25
...\.......\GetOccupiedCells.m,352,2016-10-25
...\.......\MOGWO.asv,5623,2016-10-25
...\.......\MOGWO.m,5625,2016-10-24
...\.......\results.mat,88018,2016-10-25
...\.......\RouletteWheelSelection.m,105,2016-10-25
...\.......\SelectLeader.m,577,2016-10-25
...\.......\xboundary.m,790,2016-10-25