Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning
المؤلفون المشاركون
Hao, Wei
Gao, Zhibo
Yi, Kefu
Rong, Donglei
Zeng, Qiang
Wu, Wenguang
Wei, Chongfeng
Scepanovic, Biljana
المصدر
Journal of Advanced Transportation
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-17، 17ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-09-19
دولة النشر
مصر
عدد الصفحات
17
التخصصات الرئيسية
الملخص EN
With the exponential growth of traffic data and the complexity of traffic conditions, in order to effectively store and analyse data to feed back valid information, this paper proposed an urban road traffic status prediction model based on the optimized deep recurrent Q-Learning method.
The model is based on the optimized Long Short-Term Memory (LSTM) algorithm to handle the explosive growth of Q-table data, which not only avoids the gradient explosion and disappearance but also has the efficient storage and analysis.
The continuous training and memory storage of the training sets are used to improve the system sensitivity, and then, the test sets are predicted based on the accumulated experience pool to obtain high-precision prediction results.
The traffic flow data from Wanjiali Road to Shuangtang Road in Changsha City are tested as a case.
The research results show that the prediction of the traffic delay index is within a reasonable interval, and it is significantly better than traditional prediction methods such as the LSTM, K-Nearest Neighbor (KNN), Support Vector Machines (SVM), exponential smoothing method, and Back Propagation (BP) neural network, which shows that the model proposed in this paper has the feasibility of application.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Hao, Wei& Rong, Donglei& Yi, Kefu& Zeng, Qiang& Gao, Zhibo& Wu, Wenguang…[et al.]. 2020. Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1176315
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hao, Wei…[et al.]. Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning. Journal of Advanced Transportation No. 2020 (2020), pp.1-17.
https://search.emarefa.net/detail/BIM-1176315
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Hao, Wei& Rong, Donglei& Yi, Kefu& Zeng, Qiang& Gao, Zhibo& Wu, Wenguang…[et al.]. Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1176315
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1176315
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