Kefeng Wu

TL;DR: A multi-step trajectory clustering method that combines Dynamic Time Warping, a similarity measurement method, with Principal Component Analysis to decompose the obtained distance matrix and an automatic algorithm for choosing the k clusters is developed according to the similarity distance.

TL;DR: Improved density-based spatial clustering of applications with noise (DBSCAN) algorithm is proposed to cluster spatial points to acquire the optimal cluster and a fusion of the MD, MDS, and improved DBSCAN algorithms can identify the course of trajectories and attain a better clustering performance.

TL;DR: An adaptive constrained DTW (ACDTW) algorithm is developed to calculate the distances between trajectories more accurately by introducing new adaptive penalty functions and has the best performance among three existing algorithms in modeling maritime traffic vessel trajectory.

TL;DR: An Adaptive Douglas-Peucker (ADP) algorithm with automatic thresholding for AIS-based vessel trajectory compression is proposed and comprehensive results demonstrate that the proposed algorithm can reduce the computational cost while ensuring the clustering and classification accuracy.

TL;DR: In this article , an evidence combination method based on the stochastic approach for link-structure analysis (SALSA) algorithm combined with Lance-Williams distance is proposed.