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지수형 윈도우를 이용한 연속시간 교통속도 추정 알고리즘
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 홍석교 | - |
| dc.contributor.author | 김흠 | - |
| dc.date.accessioned | 2018-11-08T06:39:57Z | - |
| dc.date.available | 2018-11-08T06:39:57Z | - |
| dc.date.issued | 2006-02 | - |
| dc.identifier.other | 1202 | - |
| dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/3350 | - |
| dc.description | 학위논문(석사)--아주대학교 일반대학원 :전자공학과,2006. 2 | - |
| dc.description.tableofcontents | 1. Introduction 1 1.1. ITS System 1 1.2. Real-time traffic estimation 3 1.3 Continuous-time traffic estimation 6 2. An Algorithm to estimate continuous-time traffic speed using Exponential Window 8 2.1. Correlated Speed Analysis 8 2.1.1. Correlation coefficient 10 2.1.2. Two-sample T test 10 2.2. Continuous-time Estimation Architecture 11 2.2.1. Estimation Architecture 11 2.2.2. Simple Window Fuction 12 2.2.3. Exponential Window Fuction 13 3. Data Modeling and Experiment 14 3.1 Simulation Method 14 3.2 Result Analysis 15 4. Conclusion 17 5. References 18 | - |
| dc.language.iso | eng | - |
| dc.publisher | The Graduate School, Ajou University | - |
| dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
| dc.title | 지수형 윈도우를 이용한 연속시간 교통속도 추정 알고리즘 | - |
| dc.title.alternative | Xin Jin | - |
| dc.type | Thesis | - |
| dc.contributor.affiliation | 아주대학교 일반대학원 | - |
| dc.contributor.alternativeName | Xin Jin | - |
| dc.contributor.department | 일반대학원 전자공학과 | - |
| dc.date.awarded | 2006. 2 | - |
| dc.description.degree | Master | - |
| dc.identifier.localId | 565177 | - |
| dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000001202 | - |
| dc.description.alternativeAbstract | Travel-Time is one of the most important parameters for Intelligent Transportation Systems (ITS), Advanced Traveler Information Systems (ATIS), and Advanced Traffic Management Systems (ATMS). Real-time vehicle speed data is measured based on loop detector in ITS studies. Accurate traffic speed data is the raw element of the travel time estimation and calculation. Real-time traffic data from loop detectors are inevitably corrupted by unexpected missing values or appear to be given nonsensical or erroneous data due to detector faults or transmission distortion. Missing data handling is an important preparation step for data mining tasks in travel time estimation. Accurate traffic speed estimation can improve the quality of estimated travel time information for ITS. In this study we present a novel algorithm to estimate continuous-time traffic speed data using Exponential Window based on the correlated speed and then compare its results to other baseline missing speed estimation methods with real freeway traffic speed data. Since this approach has greater generalization ability for given real speed data, it is believed that this model will also perform well for all time-series missing data estimation fields. | - |
- Appears in Collections:
- Graduate School of Ajou University > Department of Electronic Engineering > 3. Theses(Master)
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