THERMAL SCIENCE

International Scientific Journal

Dasi He

,

Yupeng Gou

,

Weizhi Yu

,

Sanxian Xia

,

Jie Lan

PASSENGER FLOW FORECASTING OF ZHENGZHOU METRO LINE ONE BASED ON AN IMPROVED WHALE OPTIMIZATION ALGORITHM

ABSTRACT
With the continuous expansion of urban scale in China, the increase of passenger flow has brought great pressure to the urban public transport system. An accurate and timely prediction of the short-term passenger flow at each metro station is extremely important for the metro intelligent control system to make a timely decision. In this paper, based on the measured passenger flow data of Zijingshan station of Zhengzhou Metro Line 1, an improved whale optimization algorithm is proposed to predict the passenger flow on different time scales. The results show that the method has higher accuracy than the traditional least squares support vector machines algorithm. The paper opens a new window for nowcasting warning in the rush hour and long-period optimization of the public transport.
KEYWORDS
metro passenger flow, empirical mode decomposition, improved whale optimization algorithm
PAPER SUBMITTED: 2023-05-02
PAPER REVISED: 2023-08-05
PAPER ACCEPTED: 2023-08-07
PUBLISHED ONLINE: 2024-05-18
DOI REFERENCE: https://doi.org/10.2298/TSCI2403315H
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2024, VOLUME 28, ISSUE Issue 3, PAGES [2315 - 2322]
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Passenger flow forecasting of Zhengzhou Metro Line one based on an improved whale optimization algorithm

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence