Multi-source information fusion-based urban data service system and method

Abstract

In order to achieve the purposes of unified integration, display, and management of massive cross-business data in the city, the present invention proposes a multi-source information fusion-based urban data service system and urban data processing method. The technical scheme is characterized in that: multi-source city information is preprocessed to realize information cleaning and transformation;multi-source information is initially fused through a support vector machine classifier; and an initial fusion result is further optimized through a genetic algorithm to obtain a final fusion result,and the final fusion result is displayed to users through the graphical wizard interface. According to the technical scheme of the present invention, multi-source city information fusion is realized,and information from different sources can be quickly aggregated, reorganized and correlated, so that the technical scheme can effectively serve the city information management.

Description

technical field [0001] The invention relates to a city data service system and a data processing method based on multi-source information fusion, belonging to the field of big data processing, especially the processing of big data related to smart cities. Background technique [0002] Different from the concept of "Smart City 1.0", "Smart City 2.0" puts more emphasis on real-time, comprehensive and sharing of data. Therefore, "New Smart City" usually serves the citizens full-time, efficient and orderly urban governance, and open and inclusive data. The main goals are sharing, economic development, green open source, and cyberspace security. [0003] Among them, in order to achieve the goal of "data openness, integration and sharing", it is necessary to integrate, display and manage the city's massive cross-business department data in a unified manner, generate a city fusion information resource library, and realize the unified release, on-demand subscription and exchange of ...

AI Technical Summary

Problems solved by technology

[0004] The information fusion methods in the prior art often lack adaptive adjustments in the actual fusion process of cross-platform multi-source data. For example, CN200810059244.1 discloses an evidence theory urban traffic flow information fusion method based on fuzzy rough sets, based on improved The synthesis formula of the D-S evidence theory fuses the basic probability functions of each group of evidence, and resolves conflicts between evidences, judges the reliability of relevant detectors, and selects relevant detection parameters as the fusion result according to the degree of reliability. However, it lacks robustness when using the D-S evidence theory synthesis formula to fuse the basic probability functions of each group of evidence. When the actual data is processed, when the evidence conflicts, it will produce wrong conclusions.

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