Big Data-Driven Based Real-Time Traffic Flow State Identification and Prediction
المؤلفون المشاركون
Sun, Zhi-yuan
Qu, Wen-cong
Lu, Huapu
المصدر
Discrete Dynamics in Nature and Society
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-08-03
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
With the rapid development of urban informatization, the era of big data is coming.
To satisfy the demand of traffic congestion early warning, this paper studies the method of real-time traffic flow state identification and prediction based on big data-driven theory.
Traffic big data holds several characteristics, such as temporal correlation, spatial correlation, historical correlation, and multistate.
Traffic flow state quantification, the basis of traffic flow state identification, is achieved by a SAGA-FCM (simulated annealing genetic algorithm based fuzzy c-means) based traffic clustering model.
Considering simple calculation and predictive accuracy, a bilevel optimization model for regional traffic flow correlation analysis is established to predict traffic flow parameters based on temporal-spatial-historical correlation.
A two-stage model for correction coefficients optimization is put forward to simplify the bilevel optimization model.
The first stage model is built to calculate the number of temporal-spatial-historical correlation variables.
The second stage model is present to calculate basic model formulation of regional traffic flow correlation.
A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling and computing methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Lu, Huapu& Sun, Zhi-yuan& Qu, Wen-cong. 2015. Big Data-Driven Based Real-Time Traffic Flow State Identification and Prediction. Discrete Dynamics in Nature and Society،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1060447
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Lu, Huapu…[et al.]. Big Data-Driven Based Real-Time Traffic Flow State Identification and Prediction. Discrete Dynamics in Nature and Society No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1060447
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Lu, Huapu& Sun, Zhi-yuan& Qu, Wen-cong. Big Data-Driven Based Real-Time Traffic Flow State Identification and Prediction. Discrete Dynamics in Nature and Society. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1060447
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1060447
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