HRST-LR: A Hessian Regularization Spatio-Temporal Low Rank Algorithm for Traffic Data Imputation-Reference-Cited by-同舟云学术

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HRST-LR: A Hessian Regularization Spatio-Temporal Low Rank Algorithm for Traffic Data Imputation

Published:2023-10 Issue:10 Volume:24 Page:11001-11017
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Xu Xiuqin¹^ORCID,Lin Mingwei²^ORCID,Luo Xin³^ORCID,Xu Zeshui⁴^ORCID

Affiliation:

1. School of Mathematics and Statistics, Fujian Normal University, Fujian, China

2. College of Computer and Cyber Security, Fujian Normal University, Fujian, China

3. College of Computer and Information Science, Southwest University, Chongqing, China

4. Business School, Sichuan University, Chengdu, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Fujian Province of China

Young Top Talent of Young Eagle Program of Fujian Province, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10271405/10146198.pdf?arnumber=10146198

Reference61 articles.

1. Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications

2. Adaptive Latent Factor Analysis via Generalized Momentum-Incorporated Particle Swarm Optimization

3. Highly-Accurate Community Detection via Pointwise Mutual Information-Incorporated Symmetric Non-Negative Matrix Factorization

4. Hierarchical Particle Swarm Optimization-incorporated Latent Factor Analysis for Large-Scale Incomplete Matrices

5. A Context-Aware Nonnegative Matrix Factorization Framework for Traffic Accident Risk Estimation via Heterogeneous Data

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