Subway inbound and outbound passenger flow prediction method based on deep learning

A technology of deep learning and prediction methods, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as the inability to meet the needs of station management, and achieve the effect of efficient work and high accuracy

Pending Publication Date: 2022-03-25
CASCO SIGNAL
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

Traditional station passenger flow analysis is mainly based on statistical reports, which cannot meet the needs of station management

Method used

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  • Subway inbound and outbound passenger flow prediction method based on deep learning
  • Subway inbound and outbound passenger flow prediction method based on deep learning
  • Subway inbound and outbound passenger flow prediction method based on deep learning

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Embodiment Construction

[0038] The solution proposed by the present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer from the following description. It should be noted that the drawings are in a very simplified form and all use imprecise scales, which are only used to facilitate and clearly assist the purpose of illustrating the embodiments of the present invention. In order to make the objects, features and advantages of the present invention more comprehensible, please refer to the accompanying drawings. It should be noted that the structures, proportions, sizes, etc. shown in the drawings attached to this specification are only used to match the content disclosed in the specification, for those who are familiar with this technology to understand and read, and are not used to limit the implementation of the present invention. condition, so it has no te...

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Abstract

The invention provides a subway in-out passenger flow prediction method based on deep learning. The subway in-out passenger flow prediction method comprises the steps of obtaining historical in-out passenger flow data of a plurality of target subway stations; dividing time periods by taking a preset time length as a unit, and extracting a plurality of features of the entrance / exit passenger flow volume of the target subway station in each time period from time and space dimensions to obtain each training sample; training a deep learning neural network model by using the training sample to obtain an entry / exit passenger flow prediction model of the target subway station; and adopting the entry / exit passenger flow prediction model to predict the entry / exit passenger flow of each target subway station. According to the invention, the big data technology and the deep learning algorithm are applied, and the subway station entry and exit passenger flow can be accurately predicted.

Description

technical field [0001] The present invention relates to the technical field of passenger flow forecasting, in particular to a method for predicting passenger flow in and out of subway stations based on deep learning, electronic equipment, and a computer-readable storage medium. Background technique [0002] Accurately predicting passenger flow at key stations of urban rail transit during large-scale events is an important basis for urban rail transit management and operation departments to formulate transportation organization plans, and is also the key to achieving traffic security during events. On the basis of analyzing the historical passenger flow characteristics of urban rail transit before and during large-scale events, a station passenger flow prediction model is constructed considering the characteristics of surrounding large-scale events, so as to realize the prediction of urban rail transit passenger flow during future large-scale events. Passenger flow in subway ...

Claims

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Application Information

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IPC IPC(8): G06V20/40G06K9/62G06N3/04G06N3/08G06V20/52G06V10/774
CPCG06N3/08G06N3/045G06F18/214
Inventor 张奕男袁广超张广宇何绪兰马清文朱志祥宋振江管观洋
Owner CASCO SIGNAL
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