High Dimensional Origin Destination Calibration Using Metamodel Assisted Simultaneous Perturbation Stochastic Approximation
Author:
Affiliation:
1. School of Engineering, Monash University Malaysia, Subang Jaya, Malaysia
2. School of Information Technology, Monash University Malaysia, Subang Jaya, Malaysia
3. Recogine Technology SDN BHD, Subang Jaya, Malaysia
Funder
Recogine Technology Sendirian (SDN) Berhad (BHD) [31]
School of Engineering, Monash University Malaysia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/10086684/10015895.pdf?arnumber=10015895
Reference31 articles.
1. c-SPSA: Cluster-wise simultaneous perturbation stochastic approximation algorithm and its application to dynamic origin–destination matrix estimation
2. W–SPSA in practice: Approximation of weight matrices and calibration of traffic simulation models;antoniou;Transp Res Proc,2015
3. Improving Scalability of Generic Online Calibration for Real-Time Dynamic Traffic Assignment Systems
4. Application of Principal Component Analysis to Predict Dynamic Origin–Destination Matrices
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