Dynamic clustering algorithm for geographic grids

Abstract

The invention discloses a dynamic clustering algorithm for geographic grids. The method includes the steps that firstly, the maximum longitude and latitude and the minimum longitude and latitude are found out in an area, and then according to the step length, grid division is performed on the area between the maximum longitude and latitude and the minimum longitude and latitude; serial numbers of the grids where all points are located are calculated, the points in the same grid are clustered, and the gravity center of clustering is calculated; then the grids are moved in the vertical direction and the horizontal direction, the moving lengths are kept uniform, the frequencies of moving in the directions mutually symmetrical are kept uniform, the sequence of the moving directions is not limited, after moving each time, the points, meeting clustering conditions, in the grids are clustered, and all the clustered points form a final clustered result. According to the method, the problems that a traditional clustering algorithm based on the grids is low in precision and efficiency are solved, the grids can be drawn dynamically through the method, the granularity can be freely controlled, flexibility is high, and the speed is high.

Description

technical field [0001] The application belongs to the technical field of data mining and relates to cluster analysis, in particular to a cluster analysis algorithm of a dynamic geographical grid. Background technique [0002] Cluster analysis is one of the widely researched topics in data mining. It is to find the similarity between data from the data, and classify the data accordingly, so as to discover the useful information or knowledge hidden in the data. Grid method is a commonly used method for discretizing spatial data in spatial data processing. Grid-based clustering algorithms are widely used in clustering algorithms because they are easy to implement incrementally and process high-dimensional data. [0003] Traditional geographic grid maps are a relatively simple type of map. The map area is divided into grids according to plane coordinates or latitude and longitude, and the geographic location information is described in units of grids. Extending this specific d...

AI Technical Summary

Problems solved by technology

If the division granularity of the lowest layer of the grid structure is relatively coarse and the number of grid units is relatively small, the clustering time will be reduced and the clustering speed will be fast, but the coarse granularity will reduce the clustering accuracy; on the contrary, if the grid structure If the division granularity of the lowest layer is finer, higher clustering accuracy will be obtained, but at the same time the processing overhead will increase, resulting in longer clustering time

On the other hand, if the division granularity of the lowest layer of the grid structure is too small, the number of grid cells will be increased, which may lead to too few data points falling into the grid cells, thus failing to meet the density threshold requirement and be ignored

The ant colony clustering algorithm is a commonly used algorithm for cluster analysis. The cluster analysis method based on the ant colony algorithm may run for a long time during the cluster analysis process, and the system performance that requires real-time performance cannot meet the requirements.

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