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OD flow direction clustering method based on multi-path image cutting criterion and ant colony optimization

A clustering method and criterion technology, applied in character and pattern recognition, calculation model, prediction, etc., can solve the problems of lack of measurement of semantic information, neglect of flow direction attributes, and global clustering effect needs to be improved, so as to improve the clustering effect Effect

Active Publication Date: 2021-10-19
FUZHOU UNIV
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Problems solved by technology

Common OD flow direction clustering methods often ignore the overall flow direction attribute, the global clustering effect needs to be improved, and the measurement of semantic information for flow direction is lacking

Method used

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  • OD flow direction clustering method based on multi-path image cutting criterion and ant colony optimization
  • OD flow direction clustering method based on multi-path image cutting criterion and ant colony optimization
  • OD flow direction clustering method based on multi-path image cutting criterion and ant colony optimization

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Embodiment Construction

[0053] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0054] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0055] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinatio...

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Abstract

The invention relates to an OD flow direction clustering method based on a multi-path graph cutting criterion and ant colony optimization, and the method comprises the steps: constructing a theme distribution model through a flow direction end point POI, calculating the flow direction space-time semantic similarity, constructing an undirected graph complex network and an initial pheromone matrix, extracting all connected components of the network, and recognizing connected components to be clustered; and adopting multi-process parallel mode for connected components to be clustered based on a multi-path graph cutting criterion and ant colony optimization, wherein one process clusters one connected component. Clustering results of all the processes of the steps are summarized, and a final clustering result is obtained. According to the method, an undirected graph complex network thought and a clustering algorithm are organically combined, complex network simplification is performed by adopting a Gaussian kernel function, and automatic noise identification is realized by utilizing graph connected components. According to the method, a heuristic function is improved based on a multi-path graph cutting criterion, and the initial node of the ant colony is screened by utilizing betweenness centrality based on a complex network idea, so that the clustering effect is effectively improved.

Description

technical field [0001] The invention relates to the field of urban traffic data mining and analysis, in particular to an OD flow direction clustering method based on multi-way graph cut criterion and ant colony optimization. Background technique [0002] Traffic flow is an important part of the urban comprehensive system, which contains rich potential information, and reflects the spatial distribution of the city, the characteristics of regional associations, and the travel characteristics of residents to a certain extent. Therefore, mining and analyzing the characteristics of traffic flow data is of great significance for exploring the potential laws of the city and providing suggestions for urban management. [0003] Clustering algorithm is a mainstream method of mining traffic flow data, which belongs to unsupervised learning algorithm. Through clustering, the flow directions with the same characteristics are divided into the same cluster, and the common characteristics a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/26G06K9/62G06N3/00
CPCG06Q10/04G06Q50/26G06N3/006G06F18/23
Inventor 邬群勇张晗朱秋圳
Owner FUZHOU UNIV
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