Three Revised Kalman Filtering Models for Short-Term Rail Transit Passenger Flow Prediction
المؤلفون المشاركون
Hou, Zenghao
Ibrahim, Amir
Jiao, Pengpeng
Sun, Tuo
Li, Ruimin
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-03-30
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
Short-term prediction of passenger flow is very important for the operation and management of a rail transit system.
Based on the traditional Kalman filtering method, this paper puts forward three revised models for real-time passenger flow forecasting.
First, the paper introduces the historical prediction error into the measurement equation and formulates a revised Kalman filtering model based on error correction coefficient (KF-ECC).
Second, this paper employs the deviation between real-time passenger flow and corresponding historical data as state variable and presents a revised Kalman filtering model based on Historical Deviation (KF-HD).
Third, the paper integrates nonparametric regression forecast into the traditional Kalman filtering method using a Bayesian combined technique and puts forward a revised Kalman filtering model based on Bayesian combination and nonparametric regression (KF-BCNR).
A case study is implemented using statistical passenger flow data of rail transit line 13 in Beijing during a one-month period.
The reported prediction results show that KF-ECC improves the applicability to historical trend, KF-HD achieves excellent accuracy and stability, and KF-BCNR yields the best performances.
Comparisons among different periods further indicate that results during peak periods outperform those during nonpeak periods.
All three revised models are accurate and stable enough for on-line predictions, especially during the peak periods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jiao, Pengpeng& Li, Ruimin& Sun, Tuo& Hou, Zenghao& Ibrahim, Amir. 2016. Three Revised Kalman Filtering Models for Short-Term Rail Transit Passenger Flow Prediction. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1112916
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Jiao, Pengpeng…[et al.]. Three Revised Kalman Filtering Models for Short-Term Rail Transit Passenger Flow Prediction. Mathematical Problems in Engineering No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1112916
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jiao, Pengpeng& Li, Ruimin& Sun, Tuo& Hou, Zenghao& Ibrahim, Amir. Three Revised Kalman Filtering Models for Short-Term Rail Transit Passenger Flow Prediction. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1112916
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1112916
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