Geographic position clustering method

Abstract

The invention provides a geographic position clustering method. The method comprises the steps of firstly verifying whether data in a data point set conforms to normal distribution or not; for the data conforming to the normal distribution, calculating the bandwidth of a kernel function first and then calculating a starting point of clustering; according to the starting point and the bandwidth, performing calculation to obtain an ending point which the starting point needs to be moved to; marking the accessed data in the process, and classifying the data into a cluster; if the non-accessed data exists, deleting marked points and re-calculating a new starting point; repeating the step of calculating the movement of the starting point for the first time, and obtaining an another cluster; and combining all the obtained clusters in pairs, and judging whether the clusters needed to be combined exist or not. By adopting the geographic position clustering method, abnormal points caused by incorrect extraction or other reasons can be excluded, so that correct and noiseless geographic position information is produced, and position drift caused by the fact that a geographic position producer uses different coordinate systems can be eliminated.

Description

technical field [0001] The invention belongs to the technical field of software algorithms, and in particular relates to a geographic location clustering method. Background technique [0002] With the development of computer technology, nowadays, when we need map navigation, most of us use electronic maps. After inputting a destination from the electronic map, we can directly locate the destination on the map. However, existing algorithms may have incorrect extraction or abnormal points caused by other reasons, which will lead to inaccurate geographical location data produced. Or the problem of position drift due to geolocation producers using different coordinate systems. Contents of the invention [0003] The present invention is carried out in order to solve the above-mentioned problems, and the purpose is to provide a method that can exclude abnormal points caused by incorrect extraction or other reasons, thereby producing correct and noise-free geographic location da...

AI Technical Summary

Problems solved by technology

However, the existing algorithm will have incorrect extraction or abnormal points caused by other reasons, which will lead to inaccurate geographical location data produced

Or the problem of position drift due to the use of different coordinate systems by geolocation producers

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