![](/images/graphics-bg.png)
Short-Term Origin-Destination Based Metro Flow Prediction with Probabilistic Model Selection Approach
المؤلفون المشاركون
Dai, Xiaoqing
Xu, Yanyan
Sun, Lijun
المصدر
Journal of Advanced Transportation
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-06-26
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Reliable prediction of short-term passenger flow could greatly support metro authorities’ decision processes, help passengers to adjust their travel schedule, or, in extreme cases, assist emergency management.
The inflow and outflow of the metro station are strongly associated with the travel demand within metro networks.
The purpose of this paper is to obtain such prediction.
We first collect the origin-destination information from the smart-card data and explore the passenger flow patterns in a metro system.
We then propose a data driven framework for short-term metro passenger flow prediction with the ability to utilize both spatial and temporal related information.
The approach adopts two forecasts as basic models and then uses a probabilistic model selection method, random forest classification, to combine the two outputs to achieve a better forecast.
In the experiments, we compare the proposed model with four other prediction models, i.e., autoregressive-moving-average, neural networks, support vector regression, and averaging ensemble model, as well as the basic models.
The results indicate that the proposed approach outperforms the others in most cases.
The origin-destination flows extracted from smart-card data can be successfully exploited to describe different metro travel patterns.
And the framework proposed here, especially the probabilistic combination method, can improve the performance of short-term transportation prediction.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Dai, Xiaoqing& Sun, Lijun& Xu, Yanyan. 2018. Short-Term Origin-Destination Based Metro Flow Prediction with Probabilistic Model Selection Approach. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1181471
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Dai, Xiaoqing…[et al.]. Short-Term Origin-Destination Based Metro Flow Prediction with Probabilistic Model Selection Approach. Journal of Advanced Transportation No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1181471
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Dai, Xiaoqing& Sun, Lijun& Xu, Yanyan. Short-Term Origin-Destination Based Metro Flow Prediction with Probabilistic Model Selection Approach. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1181471
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1181471
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
![](/images/ebook-kashef.png)
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
![](/images/kashef-image.png)