Road traffic condition modeling method based on fuzzy C mean value clustering algorithm

A technology of road traffic and mean value clustering, which is applied in the traffic control system of road vehicles, traffic flow detection, traffic control system, etc. Class effect, small misjudgment effect

Inactive Publication Date: 2017-09-12
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, the fuzzy c-means clustering algorithm itself has a shortcoming, that is, there is a certain blindness in the selection of the initial cluster centroid.

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  • Road traffic condition modeling method based on fuzzy C mean value clustering algorithm
  • Road traffic condition modeling method based on fuzzy C mean value clustering algorithm
  • Road traffic condition modeling method based on fuzzy C mean value clustering algorithm

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Embodiment Construction

[0027] The invention will be described in further detail below in conjunction with the accompanying drawings.

[0028] The application of the present invention is mainly manifested in the application of road traffic state recognition. Effective and accurate identification of road traffic status can help traffic management departments do a good job in traffic management, and at the same time help travelers understand road traffic status in a timely manner, which can effectively alleviate the current traffic congestion problem. Nowadays, with the continuous advancement of technology and the increase in the number of cars, a large amount of traffic data is collected every day. From these data, the current traffic status can be analyzed, which can bring great help to traffic management and traffic problem solving. . Many data mining algorithms have been used to mine the traffic status, among which the clustering algorithm is the most commonly used. Many studies use the fuzzy c-m...

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Abstract

The invention discloses a road traffic condition modeling method based on a fuzzy C mean value clustering algorithm, and belongs to the data mining technology field. By aiming at the own fuzzy performance of the road traffic condition, the fuzzy C mean value clustering algorithm is used for clustering analysis of acquired traffic data. Because of blindness of a conventional fuzzy C mean value clustering algorithm during initialization of a clustering center, a Canopy clustering algorithm is used to solve the above mentioned problem, and then a Xie-Beni index (XB index) is introduced to determine m value in a self-adaptive way, and therefore the clustering effect of the algorithm is improved, and a good data processing foundation is provided for subsequent road traffic condition identification. The road traffic condition modeling method is advantageous in that better clustering effect is provided during clustering of traffic information, and misjudgement probability is smaller, and then acquired data mining results are more accurate, and therefore the road traffic condition is reflected truly.

Description

technical field [0001] The invention belongs to the technical field of data mining, and relates to a road traffic state modeling method based on a fuzzy c-means clustering algorithm. Background technique [0002] At present, with the rapid development of the economy, earth-shaking changes have taken place in people's lives, especially in terms of outbound transportation. Private cars have become one of the most important means of transportation, so the number of cars has increased rapidly. By the end of 2015, there were 279 million motor vehicles in China, including 172 million cars. The dramatic increase in the number of cars has caused serious traffic problems. The current problems in my country's urban traffic are mainly reflected in the following aspects: (1) road traffic congestion is serious, which has seriously affected economic development, and has also caused pollution to the environment; (2) traffic management is backward, and traffic In the event of an incident, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G08G1/01
CPCG08G1/0133G06F18/23213
Inventor 黄波王青杰李大鹏李选张亚茹
Owner NANJING UNIV OF POSTS & TELECOMM
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