Title :
Mind-evolution-based machine learning and applications
Author :
Chengyi, Sun ; Yan, Sun ; Keming, Xie
Author_Institution :
Comput. Center, Taiyuan Univ. of Technol., China
Abstract :
This paper describes the foundation of proposing MEBML (mind-evolution-based machine learning) that was recently presented. Then the paper analyses the performance mechanism of MEBML which is different from GA (genetic algorithm), and its characteristics. With its own distinctive mechanism MEBML improved the efficiency and convergence rate greatly compared with GA. The paper also summarizes the recent development of researches on MEBML, which includes several different strategies of similarity and dissimilarity, the proof of convergence of MEBML and its applications. In addition the authors discuss the future work of MEBML
Keywords :
computational complexity; convergence; evolutionary computation; learning (artificial intelligence); MEBML; convergence rate; dissimilarity; mind-evolution-based machine learning; similarity; Algorithm design and analysis; Application software; Convergence; Educational institutions; Evolutionary computation; Genetic algorithms; Machine learning; Performance analysis; Sun;
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.2000.859927
