Road network operation knowledge database construction method based on artificial intelligence technology

Abstract

The invention discloses a road network operation knowledge database construction method based on artificial intelligence technology. The road network operation knowledge database comprises a data acquisition layer, a data calculation engine layer, a basic supporting layer and a knowledge application layer. The method is advantageous in that the road network operation knowledge database performs association rule mining on various factors and traffic conditions based on historical data and realizes traffic operation rule summarizing, thereby supplying decision supporting to traffic operation analysis, predication and traffic dispersion plan making, effectively improving urban traffic operation efficiency, and realizing significant meaning in improving industry traffic management level, promoting industry technology progress and expanding industry development space.

Description

technical field [0001] The invention relates to a method for constructing a knowledge base of road network operation, in particular to a method for constructing a knowledge base of road network operation based on artificial intelligence technology, and belongs to the technical field of artificial intelligence. Background technique [0002] In recent years, with the continuous improvement of the level of urban transportation informatization, the transportation industry management department has gathered a large amount of urban comprehensive traffic data. How to use the aggregated comprehensive traffic big data for in-depth analysis and application, improve the level of refinement of transportation industry management, Exploring the intelligence of traffic congestion management has become an urgent issue facing the traffic authorities. [0003] At the current stage, although many researchers at home and abroad have conducted mining analysis and application research on transpor...

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Problems solved by technology

[0003] At the current stage, although many researchers at home and abroad have conducted mining analysis and application research on transportation data such as bus data, mobile phone signaling data, and road network status data, they are all limited to the field of transportation directly related to the data. At present, big data is mainly used in shallow applications such as traffic status discrimination. Deep applications of big data such as traffic congestion analysis and congestion mitigation strategy evaluation are still in their infancy, and there is still a lack of systematic solutions in the industry. The combination of artificial intelligence technology and database cannot build a knowledge base with self-learning attributes such as reasoning, search, and clustering of artificial intelligence technology. Third, as a knowledge base for traffic operation analysis and traffic management decision-making, it cannot be used for various The function development of intelligent traffic management system provides basic tools to make urban traffic management intelligent, scientific and refined management at a low level

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