Learning to Detect Traffic Incidents from Data Based on Tree Augmented Naive Bayesian Classifiers
المؤلفون المشاركون
Hu, Xiaojian
Li, Dawei
Jin, Cheng-jie
Zhou, Jun
المصدر
Discrete Dynamics in Nature and Society
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-10-02
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
This study develops a tree augmented naive Bayesian (TAN) classifier based incident detection algorithm.
Compared with the Bayesian networks based detection algorithms developed in the previous studies, this algorithm has less dependency on experts’ knowledge.
The structure of TAN classifier for incident detection is learned from data.
The discretization of continuous attributes is processed using an entropy-based method automatically.
A simulation dataset on the section of the Ayer Rajah Expressway (AYE) in Singapore is used to demonstrate the development of proposed algorithm, including wavelet denoising, normalization, entropy-based discretization, and structure learning.
The performance of TAN based algorithm is evaluated compared with the previous developed Bayesian network (BN) based and multilayer feed forward (MLF) neural networks based algorithms with the same AYE data.
The experiment results show that the TAN based algorithms perform better than the BN classifiers and have a similar performance to the MLF based algorithm.
However, TAN based algorithm would have wider vista of applications because the theory of TAN classifiers is much less complicated than MLF.
It should be found from the experiment that the TAN classifier based algorithm has a significant superiority over the speed of model training and calibration compared with MLF.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Li, Dawei& Hu, Xiaojian& Jin, Cheng-jie& Zhou, Jun. 2017. Learning to Detect Traffic Incidents from Data Based on Tree Augmented Naive Bayesian Classifiers. Discrete Dynamics in Nature and Society،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1151843
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Li, Dawei…[et al.]. Learning to Detect Traffic Incidents from Data Based on Tree Augmented Naive Bayesian Classifiers. Discrete Dynamics in Nature and Society No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1151843
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Li, Dawei& Hu, Xiaojian& Jin, Cheng-jie& Zhou, Jun. Learning to Detect Traffic Incidents from Data Based on Tree Augmented Naive Bayesian Classifiers. Discrete Dynamics in Nature and Society. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1151843
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1151843
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر