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Affiliation of Author(s):计算机科学与技术学院/人工智能学院/软件学院

Title of Paper:A weighted DTW approach for similarity matching over uncertain time series

Journal:J. Compt. Inf. Technol.

Abstract: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. © 2018 University of Zagreb.

ISSN No.:1330-1136

Translation or Not:no

Date of Publication:2018-01-01

Co-author:Zuo, Liangli

Correspondence Author:Zuo, Liangli,yanli