@inproceedings{8fc45105066f41348fab59b9fd8af194,
title = "Using decision tree for data mining of pavement maintenance and management",
abstract = "In recent years advancements in the Information Technology (IT), have enabled automation of pavement measurement data. A large amount of data can be saved for a pavement management system. The study of pavement maintenance and management has include many methods, such as{"} expert system, decision support analysis and data mining (DM) {"}. In this study we use decision tree for data mining algorithm C5.0 has been used in this analysis. After acceptance of the decision tree, we make use of algorithms and computing for classification. This method is used to check the pavement management system database and make a comparison of all data. The result shown a correct classification of about 61% it's still improved space. According to this result we discuss three analysis results included: 1.Database information is correct or not 2.Road pavement never homogenization 3.Milling process never remove human factor. Finally useful pavement information and ways can improve system integrity and correctly.",
keywords = "Data mining, Decision tree, Pavement maintenance and management",
author = "Lin, {Jyh Dong} and Huang, {Wei Hsing} and Hung, {Chia Tse} and Chen, {Chien Ta} and Lee, {Jih Chiang}",
year = "2013",
doi = "10.4028/www.scientific.net/AMM.330.1015",
language = "???core.languages.en_GB???",
isbn = "9783037857250",
series = "Applied Mechanics and Materials",
pages = "1015--1019",
booktitle = "Materials Engineering and Automatic Control II",
note = "2nd International Conference on Materials Engineering and Automatic Control, ICMEAC 2013 ; Conference date: 18-05-2013 Through 19-05-2013",
}