DocumentCode
2192983
Title
Research on coding technology based on semantic for feature parameter optimization
Author
Jin, Ying-hao ; Sun, Li-quan
Author_Institution
Students´´ Affairs Div., Tonghua Normal Univ., Tonghua, China
fYear
2011
fDate
9-11 Sept. 2011
Firstpage
3885
Lastpage
3887
Abstract
To improve the efficiency of genetic algorithm for feature parameter optimization, a new method is presented. It determines the range of feature parameters by the availability of model, creates the coding structure of individual by model features and coding and decoding individual by features´ semantic. This method can not only improve the efficiency of coding and decoding, but also increase the evolution speed of populations. Experiments on computer show that this new method is more adaptable and practicable.
Keywords
computational geometry; decoding; feature extraction; genetic algorithms; parameter estimation; coding technology; decoding; feature parameter determination; feature parameter optimization; genetic algorithm; semantic feature modeling; Adaptation models; Computational modeling; Design automation; Educational institutions; Encoding; Optimization; Semantics; coding; feature parameter optimization; genetic algorithm; representation of semantic; semantic feature modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronics, Communications and Control (ICECC), 2011 International Conference on
Conference_Location
Ningbo
Print_ISBN
978-1-4577-0320-1
Type
conf
DOI
10.1109/ICECC.2011.6067620
Filename
6067620
Link To Document