A hub passenger flow space-time distribution prediction modeling method based on multi-source data fusion

A multi-source data, space-time distribution technology, applied in forecasting, data processing applications, character and pattern recognition, etc., can solve problems such as non-standard data object structure, difficult data association analysis, poor data interaction, etc., and achieve excellent applicability , strong standardization and complete data

Pending Publication Date: 2019-03-29
上海城市交通设计院有限公司
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Problems solved by technology

[0003] Traditional traffic data and emerging traffic-related data often have limitations such as non-standard data object structure, poor data interaction, and diverse coding, which make it difficult to form data association analysis and unify standards.

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  • A hub passenger flow space-time distribution prediction modeling method based on multi-source data fusion
  • A hub passenger flow space-time distribution prediction modeling method based on multi-source data fusion
  • A hub passenger flow space-time distribution prediction modeling method based on multi-source data fusion

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Embodiment Construction

[0049] In order to make the present invention more understandable, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings: this embodiment is implemented under the technical solution of the present invention, and the implementation process and trial effect of the present invention are given. The protection scope of the present invention is not limited to the following examples.

[0050]The present invention needs to establish the macro-level object, the meso-level object and the micro-level object of the time-space distribution of passenger flow in the hub.

[0051] The macro-objects of passenger flow distribution in hubs can be divided into regions, roads, nodes, road sections, and stations.

[0052] The area includes area code, area description, and passenger flow in different time periods;

[0053] The node includes node code, node description, and the area to which the node belongs;

[0054] The node and t...

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Abstract

The invention discloses a hub passenger flow space-time distribution prediction modeling method based on multi-source data fusion, which comprises the following steps: a multi-source data fusion database is created; the database data object comprises basic traffic and traffic related data such as mobile phone data, WIFI data, traffic card data, ticket data, road data, etc.; The macro objects of the temporal and spatial distribution model of passenger flow in the hub are created, and the macro objects include region, road, node, section and station, and the macro objects are semantically related. the macro objects are divided to get the meso objects, including inside and outside the hubs, and the corresponding multi-source data are associated; The mesoscopic region is divided into microscopic object cells according to the rules, and the relationship between the cells and the objects is created. The fused data forms a database. The invention obtains a historical database by historical data fusion, and predicts the temporal and spatial distribution of future hub passenger flow through data updating and historical data comparison. The method has the characteristics of standardization,university precision and the like.

Description

technical field [0001] The present invention relates to a prediction modeling method based on multi-source data fusion of passenger flow spatio-temporal distribution in a hub, in particular to an object type involving mobile phone data, WIFI data, traffic card data, ticketing data, and road data in the spatio-temporal distribution of passenger flow in a hub, The modeling method of spatiotemporal attributes of objects, static and dynamic attributes of the whole life cycle of objects, and semantic relations of objects. Background technique [0002] The spatio-temporal distribution of hub passenger flow is composed of a variety of traditional data, such as rail transit network and road traffic network. In recent years, with the advancement of science and technology, a variety of emerging technologies and traffic-related data have been produced. The traditional traffic data and traffic-related data of various majors and business modules are classified, centralized, and scientifi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/30G06K9/62
CPCG06Q10/04G06Q50/30G06F18/25
Inventor 董明峰贾振俞雪雷张品立朱鲤黄云付亚囡
Owner 上海城市交通设计院有限公司
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