Missing data imputation for traffic flow based on combination of fuzzy neural network and rough set theory-Reference-Cited by-同舟云学术

Missing data imputation for traffic flow based on combination of fuzzy neural network and rough set theory

Published:2020-01-27 Issue:5 Volume:25 Page:439-454
ISSN:1547-2450
Container-title:Journal of Intelligent Transportation Systems
language:en
Short-container-title:Journal of Intelligent Transportation Systems

Author:

Tang Jinjun¹,Zhang Xinshao¹,Yin Weiqi¹,Zou Yajie²,Wang Yinhai³

Affiliation:

1. Smart Transport Key Laboratory of Hunan Province, School of Traffic and Transportation Engineering, Central South University, Changsha, China

2. Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China

3. Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA

Funder

National Natural Science Foundation of China

Foundation of Central South University

Postdoctoral Science Foundation of China

Publisher

Informa UK Limited

Subject

Applied Mathematics,Computer Science Applications,Aerospace Engineering,Automotive Engineering,Information Systems,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15472450.2020.1713772

Reference41 articles.

1. New Algorithms for Filtering and Imputation of Real-Time and Archived Dual-Loop Detector Data in I-4 Data Warehouse

2. Missing data imputation using fuzzy-rough methods

3. A computer program for time series forecasting using single and double exponential smoothing techniques

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