Short-Term Passenger Flow Forecast of Rail Transit Station Based on MIC Feature Selection and ST-LightGBM considering Transfer Passenger Flow
المؤلفون المشاركون
Zhang, Yiwen
Zhang, Zhe
Wang, Cheng
Gao, Yueer
Chen, Jianwei
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-08-25
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
To solve the problems of current short-term forecasting methods for metro passenger flow, such as unclear influencing factors, low accuracy, and high time-space complexity, a method for metro passenger flow based on ST-LightGBM after considering transfer passenger flow is proposed.
Firstly, using historical data as the training set to transform the problem into a data-driven multi-input single-output regression prediction problem, the problem of the short-term prediction of metro passenger flow is formalized and the difficulties of the problem are identified.
Secondly, we extract the candidate temporal and spatial features that may affect passenger flow at a metro station from passenger travel data based on the spatial transfer and spatial similarity of passenger flow.
Thirdly, we use a maximal information coefficient (MIC) feature selection algorithm to select the significant impact features as the input.
Finally, a short-term forecasting model for metro passenger flow based on the light gradient boosting machine (LightGBM) model is established.
Taking transfer passenger flow into account, this method has a low space-time cost and high accuracy.
The experimental results on the dataset of Lianban metro station in Xiamen city show that the proposed method obtains higher prediction accuracy than SARIMA, SVR, and BP network.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhang, Zhe& Wang, Cheng& Gao, Yueer& Chen, Jianwei& Zhang, Yiwen. 2020. Short-Term Passenger Flow Forecast of Rail Transit Station Based on MIC Feature Selection and ST-LightGBM considering Transfer Passenger Flow. Scientific Programming،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1208998
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Cheng…[et al.]. Short-Term Passenger Flow Forecast of Rail Transit Station Based on MIC Feature Selection and ST-LightGBM considering Transfer Passenger Flow. Scientific Programming No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1208998
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhang, Zhe& Wang, Cheng& Gao, Yueer& Chen, Jianwei& Zhang, Yiwen. Short-Term Passenger Flow Forecast of Rail Transit Station Based on MIC Feature Selection and ST-LightGBM considering Transfer Passenger Flow. Scientific Programming. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1208998
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1208998
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