Short-Term Abnormal Passenger Flow Prediction Based on the Fusion of SVR and LSTM

Passenger flow prediction is important for the operation of urban rail transit. The prediction of abnormal passenger flow is difficult due to rare similar history data. A model based on the fusion of support vector regression (SVR) and long short-term memory (LSTM) neural network is proposed. The in...

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الحاوية / القاعدة:	IEEE Access
المؤلفون الرئيسيون:	Jianyuan Guo, Zhen Xie, Yong Qin, Limin Jia, Yaguan Wang
التنسيق:	مقال
اللغة:	الإنجليزية
منشور في:	IEEE 2019-01-01
الموضوعات:	Short-term passenger flow prediction urban rail transit support vector regression (SVR) long short-term memory (LSTM)
الوصول للمادة أونلاين:	https://ieeexplore.ieee.org/document/8675737/