Description: 轨迹聚类工具箱及其相关说明和文章（台风路径分类等）。如有问题可与wyljess@126.com联系-Trajectory clustering toolbox and related notes and articles (classification of the typhoon path, etc.). If you have any questions contact with wyljess@126.com Platform: |
Size: 8901632 |
Author:wang lei |
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Description: 轨道聚类算法的实现，增加了改进的信息，大家相互交流-Orbital clustering algorithm implementation, an increase of improved information exchanges between U.S. Platform: |
Size: 9453568 |
Author:闫珍 |
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Description: Mining trajectory data has been gaining significant interest in recent years. However, existing approaches to trajectory
clustering are mainly based on density and Euclidean distance measures. We argue that when the utility of spatial clustering of
mobile object trajectories is targeted at road-network aware location-based applications, density and Euclidean distance are no
longer the effective measures. This is because traffic flows in a road network and the flow-based density characterization become
important factors for finding interesting trajectory clusters. Platform: |
Size: 2274304 |
Author:ShAzZ |
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Description: 使用本章学习的K－平均算法，以颜色分量（或几何性状）作为坐标参数，对景象图进行聚类分析，要求最后的分类结果将路标（可能包括少量相似区域）聚类为一个模式类别。要求给出样本模式点，绘制坐标图（标出各个聚类中心的迭代移动轨迹），绘制算法框图，给出结论。并检查上机结果。-Use this learn K - average algorithm to color components (or geometric characters) as coordinate parameters, clustering analysis was carried out on the scene graph, for the final classification result will sign (may include a small amount of similar areas) clustering pattern for a category.Ask for sample model, map coordinates (mark iterative moving trajectory of every clustering center), rendering algorithm block diagram, the conclusion are given.And check the computer results. Platform: |
Size: 1727488 |
Author:张煊宜 |
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Description: 船舶AIS轨迹提取，作出船舶AIS轨迹图。在此基础上，实现基于空间相似距离的K均值轨迹聚类。算法可以自定义轨迹聚类初始轨迹或者由程序随机生成初始轨迹，采用迭代的方法直到确定最终的聚类中心。-The extraction of ship AIS trajectory, make ship AIS trajectories. On this basis, to achieve similar K mean trajectory clustering based on distance space. You can customize the initial trajectory trajectory clustering algorithm or randomly generated by the program initial trajectory, iterative method was used to determine the cluster center until the end.
Platform: |
Size: 66560 |
Author:张春辉 |
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Description: 基于密度的轨迹聚类，可以将轨迹进行分类，代码齐全，可供参考(Based on the density of trajectory clustering, trajectory can be classified, the code is complete, for reference) Platform: |
Size: 2113536 |
Author:swtab |
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Description: Java implementation for DBSCANSD, a trajectory clustering algorithm.
DBSCANSD (Density-Based Spatial Clustering of Applicationswith Noise considering Speed and Direction)[1] is a clustering algorithm extended from DBSCAN [2]. It can consider speed and direction, which is essential for maritime lanes extraction. The output of this algorithm is a set of Gravity Vectors (GV) and Sampled Stopping Points (SSP).
In the present version, the implementation has not included generating SSP yet, but I shall add this part later.
Since the AIS data provided for this project is confidential, I cannot upload it to github as example. But I generated a toy data set and put it in the src folder which can be tested with the program. And it will be great if you use this algorithm for other domains' problems, such as tracking data of vehicles, pedestrian, hurricane or animals.
More details about this algorithm can be found in [1]. The link is as following:
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7004281
Platform: |
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Author:648577896 |
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Description: # How To Run The Code ?
After downloading it to local,
1. cd to the folder of src/boliu/dbscansd/
2. compile all the .java files using:
javac *.java
3. cd to the folder of src/
4. execute the program using the following either command:
java boliu.dbscansd.Main inputfile outputfile lineNum eps minPts maxSpd maxDir isStop
* @param inputfile the input file path
* @param outputfile the output file path
* @param lineNum the designated number of trajectory points for clustering (if the size of the input file is less than lineNum, it will extract all the points)
* @param eps 1st parameter of DBSCANSD, the radius
* @param minPts 2nd parameter of DBSCANSD, the minimum number of points
* @param maxSpd 3rd parameter of DBSCANSD, the maximum SOG difference
* @param maxDir 4th parameter of DBSCANSD, the maximum COG difference
* @param isStop boolean value (0/1), if you would like to cluster stopping points (1) or moving points (0)
--e.g. java boliu.dbscansd.Main toy_data.csv output 70000 0.03 50 2 2.5 0
In this way, the program will do the job on toy_data.csv file.
It will extract the first 70,000 moving points from the data and then run DBSCANSD on the dataset.
The final output will be two files:
output_gv.csv (gravity vectors)
output_movingclusters.csv (original clustering results with more rows).
5. waiting for the result :) The running time will vary with different sizes of the input data and other input parameters.
6. Star it if it helps \*-\* Platform: |
Size: 11994582 |
Author:648577896 |
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Search - trajectory clustering