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.
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;
Conference_Titel :
Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0475-4
DOI :
10.1109/COGINF.2006.365575
