DocumentCode
2678032
Title
Convergence Analysis of Mind Evolutionary Algorithm Based on Functional Analysis
Author
Xie, Keming ; Qiu, Yuxia ; Xie, Gang
Author_Institution
Coll. of Inf. Eng., Taiyuan Univ. of Technol.
Volume
2
fYear
2006
fDate
17-19 July 2006
Firstpage
707
Lastpage
710
Abstract
As one of new type evolutionary computing methods, mind evolutionary algorithm processes evolutionary operations by using ´similartax´ and ´dissimilation´ operator. This paper studies the variance of population during the evolution from the view of the functional analysis. Interval sheath theorem is used to prove the global convergence of the algorithm. The conclusion is validated again by the numerical experiment results
Keywords
convergence; evolutionary computation; functional analysis; mathematical operators; convergence analysis; dissimilation operator; functional analysis; interval sheath theorem; mind evolutionary algorithm; population variance; similartax operator; Algorithm design and analysis; Convergence; Educational institutions; Evolutionary computation; Functional analysis; Gaussian distribution; Humans; Learning systems; Nonhomogeneous media; Scattering parameters; Convergence; Interval sheath theorem; Mind evolutionary algorithm; Sequence;
fLanguage
English
Publisher
ieee
Conference_Titel
Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
1-4244-0475-4
Type
conf
DOI
10.1109/COGINF.2006.365575
Filename
4216493
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