Incident Duration Modeling Using Flexible Parametric Hazard-Based Models
المؤلفون المشاركون
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-11-04
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
Assessing and prioritizing the duration time and effects of traffic incidents on major roads present significant challenges for road network managers.
This study examines the effect of numerous factors associated with various types of incidents on their duration and proposes an incident duration prediction model.
Several parametric accelerated failure time hazard-based models were examined, including Weibull, log-logistic, log-normal, and generalized gamma, as well as all models with gamma heterogeneity and flexible parametric hazard-based models with freedom ranging from one to ten, by analyzing a traffic incident dataset obtained from the Incident Reporting and Dispatching System in Beijing in 2008.
Results show that different factors significantly affect different incident time phases, whose best distributions were diverse.
Given the best hazard-based models of each incident time phase, the prediction result can be reasonable for most incidents.
The results of this study can aid traffic incident management agencies not only in implementing strategies that would reduce incident duration, and thus reduce congestion, secondary incidents, and the associated human and economic losses, but also in effectively predicting incident duration time.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Li, Ruimin& Shang, Pan. 2014. Incident Duration Modeling Using Flexible Parametric Hazard-Based Models. Computational Intelligence and Neuroscience،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1034654
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Li, Ruimin& Shang, Pan. Incident Duration Modeling Using Flexible Parametric Hazard-Based Models. Computational Intelligence and Neuroscience No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1034654
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Li, Ruimin& Shang, Pan. Incident Duration Modeling Using Flexible Parametric Hazard-Based Models. Computational Intelligence and Neuroscience. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1034654
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1034654
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