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Passenger route prediction algorithm

A passenger and route technology, applied in the field of passenger route prediction system, can solve the problem of lack of related research and so on

Inactive Publication Date: 2016-10-26
SICHUAN UNIV
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  • Abstract
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AI Technical Summary

Problems solved by technology

The scale-free characteristics of human space movement behavior are determined by the scale-free characteristics of the infrastructure network itself, but this conclusion lacks sufficient evidence
On the ground transportation network, there have been some studies on the prediction of the passenger's next location, but there is no relevant research on the prediction of the passenger's route on the air transportation network

Method used

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Embodiment Construction

[0010] figure 1 Among them, the route predicted for the passenger route uses the travel data of passengers, and through big data preprocessing, part of the data is used for analysis and modeling, and the other part is used to verify the effectiveness of the model. Hypothesis testing is adopted, and multi-agent technology simulation is used to explore the passenger's itinerary distribution characteristics and travel influencing factors. In the study of individual characteristics, the information entropy and statistical learning methods are used to mine the flight patterns of passengers and the theoretical predictable values ​​are calculated. Finally, using the methods of machine learning and human dynamics, a route prediction model is proposed.

[0011] figure 2 , is the flow chart of passenger route prediction algorithm. According to the relationship between the departure airport and the destination airport of the passenger's current route and the passenger's Home, predict...

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Abstract

The invention relates to a passenger personal route prediction algorithm, which can be used for predicting next route selection of a passenger. In the fundamental research, an attraction model is put forward, and the influence of an infrastructure network on travel is considered. Experimental papers show that travel distribution characteristics of people result from the infrastructure network. According to the passenger route prediction algorithm, a next route of the passenger is predicted, predictions are carried out separately through comparing the relationship among a departure airport, a destination airport and Home of a current route, and the flight characteristics of the passenger are fully considered. When the destination airport of the current route equals to the Home, the current state of the passenger, weeks and time periods of a last departure, attraction of cities and time distance are taken into account and are represented by formulas. The passenger takes the cluster characteristics and the distance between airports into account when selecting a new route, and selects the airport through selecting the next most likely distance. The experiment shows that average prediction precision of a model can reach 68%, and that the prediction is relatively stable through changing experimental environments and changing the predicted length and predicted number of people.

Description

Technical field [0001] The invention relates to a passenger route prediction system, which is to predict the passenger's next route selection. Background technique [0002] In recent years, information technology has been widely used in all walks of life, and the speed of data growth is getting faster and faster. The huge amount of data poses challenges to massive data processing technology. In the civil aviation transportation industry, with the deepening of the information construction of various airports and airlines, a large number of digital traces of passenger travel generated by electronic equipment have been preserved, and the data scale has reached the PB level, with the scale, diversity and high speed of big data. Three characteristics. The distribution of civil aviation traffic is closely related to passenger travel, and the big data of the civil aviation industry implies a large amount of passenger travel pattern information. Existing traffic distribution model...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04
CPCG06Q10/04
Inventor 彭舰陈继德宁黎苗陈瑜李梦诗黄飞虎徐文政刘唐黎红友
Owner SICHUAN UNIV