Abstract
The development of big data technology provides more economical and effective methods for network optimization. Firstly, the platform logic architecture and the main functions of the network optimization platform based on rasterized big data are described. Then the key technical scheme of the platform is introduced. By rasterizing MR, the regional accuracy of the location problem is effectively improved, which is up to 50*50 m. By matching quality indicators and perception indicators to the grid presentation, we can build grid-level network, perception and value three-dimensional analysis capabilities, and more accurately combine perception and value dimensions to tract network optimization and planning. Finally, some application scenarios and cases are described to show the role of the platform in intelligent network optimization.
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