Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Passenger flow volume prediction method and device

A technology for passenger flow and forecasting results, which is applied in traffic control systems, instruments, traffic control systems, etc. of road vehicles, can solve the problem of low accuracy of passenger flow, and achieve the effect of improving accuracy

Active Publication Date: 2016-04-20
深圳市北斗智能科技有限公司
View PDF4 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present invention provide a method and device for predicting passenger flow to solve the problem that the prediction method of passenger flow in the prior art is based on single-source data, resulting in relatively low accuracy in predicting passenger flow

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Passenger flow volume prediction method and device
  • Passenger flow volume prediction method and device
  • Passenger flow volume prediction method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0024] Please refer to figure 1 , a method for predicting passenger flow provided by an embodiment of the present invention may include:

[0025] 110. Acquire characteristic attributes affecting passenger flow in multi-source data, where the multi-source data includes smart card swiping data, weather data, and vehicle GPS data.

[0026] There are many factors that affect passenger flow, such as weather conditions, road traffic congestion, these factors will affect the future passenger flow. In the embodiments of the present invention, by acquiring smart card swiping data, meteorological data and motor vehicle GPS data, and predicting passenger flow based on the characteristic attributes of these data, the accuracy of prediction can be better improved.

[0027] In some embodiments of the present invention, the passenger flow is specifically subway passenger flow.

[0028] In some embodiments of the present invention, the smart card swiping data includes: the unique identifica...

Embodiment 2

[0085] Please refer to Figure 4 , the embodiment of the present invention provides a passenger flow forecasting device 40, which may include:

[0086] Obtaining module 41, is used for obtaining the feature attribute that influences passenger flow in multi-source data, and described multi-source data comprises smart card swiping data, meteorological data and motor vehicle GPS data;

[0087] The prediction module 42 uses the autoregressive integral moving average model and the artificial neural network to predict the future passenger flow based on the characteristic attributes obtained in the acquisition module.

[0088] see Figure 5 , in some embodiments of the present invention, the acquisition module 41 includes:

[0089] The classification unit 411 is used to classify the passengers into frequent passengers and individual passengers based on the smart card swiping data, and count the number of frequent passengers and individual passengers;

[0090] Weather index unit 41...

Embodiment 3

[0111] An embodiment of the present invention also provides a computer-readable medium, including computer-executable instructions, so that when a processor of a computer executes the computer-executable instructions, the computer executes the method flow of the method for predicting passenger flow in Embodiment 1.

[0112] To sum up, the method and device for predicting passenger flow in the embodiment of the present invention, based on the characteristic attributes affecting passenger flow in multi-source data, uses the autoregressive integral sliding average model and artificial neural network to predict future passenger flow, which can improve the predicted passenger flow the accuracy.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a passenger flow volume prediction method and device, and the method and device are used in the technical field of passenger flow volume prediction. In some feasible embodiment of the invention, the method comprises the steps: obtaining characteristic attributes, affecting the passenger flow volume, from multi-source data, wherein the multi-source data comprises an intelligent card swiping data, meteorological data, and motor vehicle GPS data; and predicting the future passenger flow volume based on the characteristic attributes through employing an autoregression integration moving average model and an artificial neural network. According to the technical scheme of the invention, the method and device can predict the future passenger flow volume based on the characteristic attributes through employing the autoregression integration moving average model and the artificial neural network, and can improve the prediction precision of the passenger flow volume.

Description

technical field [0001] The invention relates to the technical field of passenger flow forecasting, in particular to a passenger flow forecasting method and device. Background technique [0002] As an important part of public transportation, rail transit has the characteristics of fast speed, accurate time, large transportation volume, long transportation distance, high comfort, and little influence from the outside world. It plays an important role and has increasingly become the preferred mode of transportation for citizens to travel. With the increase of subway passenger flow day by day, rail transit is also suffering from serious passenger flow congestion, and the complexity of passenger flow organization is getting higher and higher. Therefore, the subway passenger flow The short-term forecast of traffic volume reflects the incomparable role of other modes of transportation, and is an important reference factor for formulating transport capacity allocation plans and pass...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G08G1/00
Inventor 赵娟娟张帆须成忠
Owner 深圳市北斗智能科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com