%0 Journal Article
%T A Weighted DTW Approach for Similarity Matching over Uncertain Time Series
%A Yan
%A Li
%A Zuo
%A Liangli
%J -
%D 2018
%R 10.20532/cit.2018.1004217
%X Sa£żetak To measure uncertain time series similarity effectively and efficiently, in this paper, we propose a weighted DTW distance-based approach for uncertain time series with the expected distance. We introduce a weight function to assign weights to a reference point and a testing point. With this function and the WDTW, the accuracy of calculating uncertain time series similarity can be improved. Also, to reduce the storage space and time-consuming, we extend the lower bound function LB_Keogh for DTW into ULB_Keogh for our approach
%K uncertain time series
%K similarity matching
%K dynamic time warping (DTW)
%K weighted DTW
%U https://hrcak.srce.hr/index.php?show=clanak&id_clanak_jezik=312287