Modeling of a stereo vision system using a genetic algorithm based fuzzy linear regression
Contribuinte(s) |
[Unknown] |
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Data(s) |
01/01/2007
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Resumo |
In this paper a fuzzy linear regression (FLR) model integrated with a genetic algorithm (GA) is proposed. The proposed GA-FLR model is applied to modeling of a stereo vision system. A set of empirical data from stereo vision object measurement is collected based on the full factorial design technique. Three regression models, namely ordinary least-squares regression (OLS), FLR, and GA-FLR, are developed, and with their performances compared. The results show that the proposed GA-FLR model performs better than OLS and FLR in modeling of a stereo vision system.<br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
[The Conference] |
Relação |
http://dro.deakin.edu.au/eserv/DU:30050252/kho-modelingofa-2007.pdf http://eprints.usm.my/14831/1/paper7.pdf |
Palavras-Chave | #fuzzy linear regression #genetic algorithm #stereo vision #range finder #factorial design |
Tipo |
Conference Paper |