Subway short-term passenger flow forecasting method based on LS-SVM and real-time big data

A forecasting method and big data technology, applied in forecasting, data processing applications, calculations, etc., can solve problems such as ignoring subway passenger flow classification, real-time judgment of incoming passenger flow change trends, impacting station and line passenger flow prediction, etc., to achieve accuracy and high real-time effects

Active Publication Date: 2019-02-05
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

[0011] Existing methods only predict based on historical passenger flow and real-time inbound passenger flow. The shortcoming is that there is no judgment on the change trend of real-time inbound passenger flow, which affects th

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  • Subway short-term passenger flow forecasting method based on LS-SVM and real-time big data
  • Subway short-term passenger flow forecasting method based on LS-SVM and real-time big data
  • Subway short-term passenger flow forecasting method based on LS-SVM and real-time big data

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Embodiment Construction

[0078] The object of the invention of the present invention will be further described in detail below in conjunction with specific embodiments.

[0079] Such as figure 1 As shown, a short-term subway passenger flow prediction method based on LS-SVM and real-time big data, including steps:

[0080] Step 1. Obtain the IC card swiping data of the AFC system, obtain the passenger's entry and exit station, entry and exit time, and obtain the OD coefficient of the passenger's historical travel station;

[0081] Step 2, for the passengers involved in the route selection of the circular line, the Logit model is used to calculate the route selection probability;

[0082] Step 3: Use historical OD coefficients to train the LS-SVM model to obtain the predicted distribution of inbound passengers and the uplink and downlink ratio coefficients of the lines; use the inbound and outbound passenger flow data to train the LS-SVM model to obtain the predicted volume of passenger inbound and out...

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Abstract

The invention discloses subway short-term passenger flow forecasting method based on LS-SVM and real-time big data. The method includes the following steps: (1) obtaining passenger in-out time and passenger out-in time, and obtaining passenger historical travel station OD coefficient; 2, adopt a Logit model to calculate that route selection probability of passengers involved in the route selectionof the ring line; 3, By using the historical OD coefficient to train the LS-SVM model to obtain the ratio coefficient of up-to-down route and up-to-down route. Using passenger flow data in and out ofthe station to train LS-SVM model to obtain the passenger entry and exit forecasts. 4, calculate that transfer ratio of the transfer station by adopting the OD coefficient and the Logit model, and carry out correction through the real-time video identification technology; Step 5, obtaining the distribution of passengers in the road network and updating the road network. The invention obtains useful real-time data through a screening system and corrects the prediction result, thereby obtaining the prediction result with higher accuracy and real-time performance.

Description

technical field [0001] The invention provides a short-term subway passenger flow prediction method based on LS-SVM and real-time big data, that is, provides a method for predicting passenger flow at subway stations and line sections based on AFC swiping card data and path selection probability, and belongs to the field of computer application technology. Background technique [0002] With the rapid development of urban subway construction, the subway network has become complex, and the routes available for travel are diversified. Short-term line passenger flow is very important to passenger route selection. If passengers can know the passenger flow of subway stations and lines in 5 minutes, 30 minutes, or even 60 minutes, they can adjust their travel plans in time according to the predicted passenger flow and avoid Congested lines can achieve the purpose of balancing passenger flow for the subway network. The short-term subway passenger flow forecast can promptly remind the...

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Application Information

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IPC IPC(8): G06Q10/04
CPCG06Q10/04
Inventor 温惠英张东冉李海欣
Owner SOUTH CHINA UNIV OF TECH
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