Semi-parametric linear mixed effects model for vehicles identification

Yow-Jen Jou*, Chai-Tzu Yang, Chien-Chia Huang, Jennifer Yuh-Jen Wu

*Corresponding author for this work

研究成果: Chapter同行評審

摘要

In order to make the detecting of the lanes and the types of the vehicles traveling on various roadways affordable, radio-frequency (RF) system-on-chip is designed and will be mounted on the roadside to collect vehicle information. We use the Fast Fourier Transform (FFT) to transform the signal of the reflecting wave radar into the numerical data, and utilize it by the statistical approach to discriminate the size of cars and the lanes. In order to classify the types of the vehicles, two models are proposed to model the data. One is multivariate analysis of variance model to account for the main effect and the interaction effect between type and lane, the other is the semi-parametric linear mixed effect model to emphasize the functional characteristic of the data. Both models work well when the number of groups is small but deteriorate when the number of groups increases.
原文English
主出版物標題Computation In Modern Science And Engineering Vol 2, Pts A And B
編輯G Maroulis, TE Simos
頁面984-+
2
DOIs
出版狀態Published - 2007
事件International Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007 - Corfu, Greece
持續時間: 25 九月 200730 九月 2007

出版系列

名字AIP Conference Proceedings
2
ISSN(列印)0094-243X

Conference

ConferenceInternational Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007
國家Greece
城市Corfu
期間25/09/0730/09/07

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