Data adaptive functional outlier detection: Analysis of the Paris bike sharing system data

Liu，Chao1; Gao，Xiao2; Wang，Xiaokang3

2022-07-01

10.1016/j.ins.2022.04.029

INFORMATION SCIENCES   影响因子和分区

0020-0255

1872-6291

Bike sharing systems (BSSs) have become an increasingly popular means of sustainable transportation, and have been implemented in many cities worldwide. Our approach contributes to the identification of abnormal patterns by applying real-time occupancy data from Paris. In particular, we propose a novel functional outlier detection algorithm based on a two-step approach: In the first stage, a clean dataset is obtained based on the combined effect of two extreme statistics calculated from random sampling; in the second stage, a multiple testing approach based on the clean dataset is proposed, in which the false discovery rate (FDR) control procedure is used to adaptively choose the thresholds for the hypothesis tests. Extensive numerical simulations were conducted to compare the outlier detection performance with those of other state-of-art methods. The proposed approach is then applied to the Paris Vélib’ bike sharing system dataset to identify abnormal patterns that are of particular interest to BSS operators for identifying system inefficiencies and update policies.

Bike sharing systems False discovery rate (FDR) control Functional data analysis Outlier detection

SCI ; EI

英语

第一

China Postdoctoral Science Foundation["2021M691443","2021TQ0141"]

Computer Science

Computer Science, Information Systems

WOS:000796651500002

ELSEVIER SCIENCE INC

20221812067022

Adaptive control systems ; Anomaly detection ; Bicycles ; Data handling ; Numerical methods ; Sampling ; Statistical tests

Passenger Highway Transportation:432.2 ; Data Processing and Image Processing:723.2 ; Control Systems:731.1 ; Numerical Methods:921.6 ; Mathematical Statistics:922.2

COMPUTER SCIENCE

2-s2.0-85129286765

Scopus

1.Department of Statistics and Data Science,Southern University of Science and Technology,Shenzhen,China
2.Department of Statistics,University of California,Riverside,United States
3.School of Economics and Management,Beijing University of Posts and Telecommunications,Beijing,China

Liu，Chao,Gao，Xiao,Wang，Xiaokang. Data adaptive functional outlier detection: Analysis of the Paris bike sharing system data[J]. INFORMATION SCIENCES,2022,602:13-42.

Liu，Chao,Gao，Xiao,&Wang，Xiaokang.(2022).Data adaptive functional outlier detection: Analysis of the Paris bike sharing system data.INFORMATION SCIENCES,602,13-42.

Liu，Chao,et al."Data adaptive functional outlier detection: Analysis of the Paris bike sharing system data".INFORMATION SCIENCES 602(2022):13-42.