Multi-source heterogeneous data fusion method and system for urban brain scene
A multi-source heterogeneous data, multi-source data technology, applied in other database retrieval, other database indexing, special data processing applications, etc., can solve problems such as inability to integrate, data is not unified, etc., to achieve the effect of enhancing connotative value
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example 1
[0090] Based on the use of population comprehensive governance scenarios
[0091] The comprehensive management of urban population needs massive data support, including static population attribute information, residential information, flow information, and location information. Based on data fusion and analysis, the population size, structure, correlation index, and temporal and spatial distribution are realized. Analytical support capabilities in different dimensions ultimately assist urban population governance and monitoring management.
[0092] Including the following steps:
[0093] 1) Build a population theme resource database, and logically classify the database according to business logic;
[0094] 2) Integrate population data, unify the data format and transform coordinates through tools;
[0095] 3) Establish attribute field mapping between different data sources;
[0096] 4) Mount processing of non-spatial data;
[0097] 5) Data element merging, deletion and fus...
example 2
[0101] Research Scenarios of Resumption of Work and Production Indicators after the Epidemic Based on Multi-source Data Fusion
[0102] Including the following steps:
[0103] 1) Under the influence of the current epidemic situation, enterprises are gradually recovering from work and production, and it is necessary to be able to use massive and complex multi-source heterogeneous data to support the analysis and decision-making of economic operation indicators;
[0104] 2) Judging its operation trend, coordinating census data, housing data, traffic data, communication data, power data, and spatializing data;
[0105] 3) Extract and integrate attributes that can quantify and analyze economic indicators, assist managers in rationally allocating resources, strengthen forecasting and early warning, and do a good job in structural optimization and stability.
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