文件名称:NEA
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- 上传时间:2008-10-13
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文件大小:37.14kb
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针对现有遗传算法在多维非线性优选方面的不足,本文提出了一种基于小生境进化算法(NEA)的非线性优选模型,探讨了NEA算法的参数选择原则。通过大量仿真和比较,表明算法在复杂非线性优选中具有快速、高效、鲁棒性强的特点,并能在全局范围内有效搜索所有最优解。
-against existing genetic algorithms in three-dimensional nonlinear optimization for the shortage, the paper presents a niche evolutionary algorithm (NEA) nonlinear optimization model, the NEA on the parameters chosen algorithm principle. Through simulation and large, the algorithm shown in a complex nonlinear optimization is fast, efficient, robust features of the strong, and the global scope effective search all the optimal solution.
-against existing genetic algorithms in three-dimensional nonlinear optimization for the shortage, the paper presents a niche evolutionary algorithm (NEA) nonlinear optimization model, the NEA on the parameters chosen algorithm principle. Through simulation and large, the algorithm shown in a complex nonlinear optimization is fast, efficient, robust features of the strong, and the global scope effective search all the optimal solution.
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下载文件列表
Debug/
EP.APS
EP.clw
EP.cpp
EP.dsp
EP.dsw
EP.h
EP.ncb
EP.opt
EP.rc
EP2bestResult.txt
EP2Result.txt
EPDlg.cpp
EPDlg.h
example2.txt
ReadMe.txt
res/
resource.h
Result_30var-32success.txt
Result_30var-32success2.txt
Result_30var-32success3.txt
Result_30var1001-19.txt
Result_30var1001-31.txt
Result_30var1001.txt
Result_onevar.txt
Result_threevar.txt
res/EP.ico
res/EP.rc2
StdAfx.cpp
StdAfx.h
EP.APS
EP.clw
EP.cpp
EP.dsp
EP.dsw
EP.h
EP.ncb
EP.opt
EP.rc
EP2bestResult.txt
EP2Result.txt
EPDlg.cpp
EPDlg.h
example2.txt
ReadMe.txt
res/
resource.h
Result_30var-32success.txt
Result_30var-32success2.txt
Result_30var-32success3.txt
Result_30var1001-19.txt
Result_30var1001-31.txt
Result_30var1001.txt
Result_onevar.txt
Result_threevar.txt
res/EP.ico
res/EP.rc2
StdAfx.cpp
StdAfx.h
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