Title :
Research of the dissimilation strategy for MEBML
Author :
Jianchao, Zeng ; Kai, Zha
Author_Institution :
Div. of Syst. Simulation & Comput. Appl., Taiyuan Heavy Machine Inst., China
Abstract :
MEBML, mind-evolution-based machine learning mainly consists of similar taxis and dissimilation operators. Especially, the dissimilation strategy has important effects on the evolution efficiency and global optimality. In the paper, five dissimilation strategies based on the analysis of effects of the dissimilation operator in MEBML and the dissimilation mechanism. Finally, comparisons of these dissimilation strategies are made through the example of a global optimization problem
Keywords :
evolutionary computation; learning (artificial intelligence); optimisation; MEBML; dissimilation operator; dissimilation strategies; dissimilation strategy; evolution efficiency; global optimality; global optimization problem; mind-evolution-based machine learning; similar taxis operator; Computational modeling; Computer applications; Computer simulation; Evolutionary computation; Machine learning; Machinery;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.859931
