Inferring origin-destination distribution of agent transfer in a complex network using deep gated recurrent units

• Main Authors: Saw, Vee-Liem, Vismara, Luca, Suryadi, Yang, Bo, Johansson, Mikael, Chew, Lock Yue
• Other Authors: School of Physical and Mathematical Sciences
• Format: Article
• Language: English
• Published: 2023
• Subjects: Science::Physics; Deep Neural Network; Gated Recurrent Unit Network
• Online Access: https://hdl.handle.net/10356/169226
• Institution: Nanyang Technological University

Predicting the origin-destination (OD) probability distribution of agent transfer is an important problem for managing complex systems. However, prediction accuracy of associated statistical estimators suffer from underdetermination. While specific techniques have been proposed to overcome this defi...