Azam Amir received "Excellent Presentation Award" at 2023 Japan Society of Civil Engineers Annual Meeting.

2023/11/28
  • Regional Environment Systems

Awardee
Azam Amir (Regional Environment Systems Course/Doctoral course, 3rd Year)

Faculty supervisor
Professor Michael Henry (Dept. of Civil Engineering)

Conference name

2023 Japan Society of Civil Engineers Annual Meeting

Award
Excellent Presentation Award

【Title of Paper

Utilization of ANN and Markov Chain-based pavement performance models for network-level maintenance management

Azam

Purpose of the Research

This research focused on the theme of data-driven maintenance management, aiming to enhance effective maintenance strategies. Two widely used approaches, the Markov chain method and the Artificial Neural Network, were employed to develop pavement condition prediction models. Subsequently, the implications and limitations of both models were discussed from a network-level management perspective.

Research Summary

The research aimed to enhance maintenance strategies through data-driven methods, utilizing the Markov chain and Artificial Neural Network approaches to develop pavement condition prediction models. The study discussed the implications and limitations of these models from a network-level management perspective, providing insights for effective maintenance decision-making.


Future Prospects 

The research aimed to assist pavement engineers in deciding the most suitable approach based on their specific objectives. Given the common use of the Markov chain method and Artificial Neural Network in pavement condition prediction modeling, the research's utilization, implications, and limitations section is particularly designed to help pavement engineers understand when to employ a specific approach.

Azam Amir
‪DR. AMIR AZAM‬ - ‪Google Scholar‬
Azam AMIR | Researcher | Doctor of Philosophy | Shibaura Institute of Technology, Kōtō-ku | Department of Civil Engineering | Research profile (researchgate.net)