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دسته بندی:
تشخیص الگو - Pattern recognition
سال انتشار:
2019
عنوان انگلیسی مقاله:
A trajectory clustering method based on Douglas-Peucker compression and density for marine traffic pattern recognition
ترجمه فارسی عنوان مقاله:
روش خوشه بندی مسیر مبتنی بر فشرده سازی و تراکم داگلاس-پوکر برای تشخیص الگوی ترافیک دریایی
منبع:
Sciencedirect - Elsevier - Ocean Engineering, 172 (2019) 456-467: doi:10:1016/j:oceaneng:2018:12:019
نویسنده:
Liangbin Zhao, Guoyou Shi∗
چکیده انگلیسی:
Clustering analysis is applied extensively in pattern recognition. In marine traffic applications, the clustering
results may exhibit a customary route and traffic volume distribution. In order to improve the clustering performance
of ship trajectory data, which is characterized by a large data volume and distribution complexity, a
method consisting of Douglas-Peucker (DP)-based compression and density-based clustering is proposed. In the
first part of the proposed method, the appropriate parameters for the DP algorithm were determined according
to the shape changes in the trajectories, which were used to compress the trajectories prior to calculating the
dynamic time warping (DTW) distance matrix. In the second part, the density-based spatial clustering of applications
with noise (DBSCAN) algorithm was improved in terms of determining the parameters. Based on the
statistical characteristics of ship trajectory distribution, the appropriate DBSCAN parameters could be determined
adaptively. Evaluation and comparison experiments were conducted based on massive real ship trajectories
in the Chinese port of Beilun-Zhoushan. The results demonstrated that, compared to the traditional
DTW distance, the proposed similarity measurement exhibits superior performance in terms of both time and
quality. Furthermore, the results of the comparison experiment demonstrated that the improved DBSCAN outperforms
two existing clustering methods in marine traffic c pattern recognition.
Keywords: Ship trajectory clustering | Douglas–peucker algorithm | DBSCAN | DTW
قیمت: رایگان
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