QB模型 神经网络

代码说明：

说明：  从数据库获取车辆在一段时间内的所有行驶记录的相关数据，确定所需数据为GPS经纬度坐标和驾驶时长等，QB模型采用MDF的思想,其基本思想为:通过平均直接翻转距离函数定义两条轨迹之间的距离，两条轨迹需要具有相同的经纬度点数，具有相同点数的轨迹最大的优点是对轨迹距离成对计算，且相同轨迹之间具有更高的分辨率，对于轨迹聚类的结果有一定的优化。(Retrieved from the database cars all over a period of time, record the related data, determine the required data for the GPS latitude and longitude coordinates, and the driving time, QB model by adopting the idea of MDF, its basic idea is: flip directly by the average distance function definition of the distance between two trajectories, two tracks will have the same latitude and longitude points, and has the biggest advantages of the same points of trajectory track distance calculation in pairs, and has higher resolution, between the same trajectory for trajectory clustering results have certain optimization.)

文件列表：

qb神经网络\GPSDistance.py, 1542 , 2019-07-03
qb神经网络\oneUserMap.html, 1127617 , 2019-07-16
qb神经网络\plot_map.py, 1891 , 2019-05-21
qb神经网络\quickBundleCluster(1).py, 3832 , 2019-07-16
qb神经网络\segment_clustering_features.py, 11393 , 2019-07-20
qb神经网络\segment_quickbundles (4).py, 5099 , 2019-07-20
qb神经网络, 0 , 2019-07-20