Advanced Artificial Intelligence and Mathematical Modeling for Risk and Resilience Problems in Infrastructures
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".
Deadline for manuscript submissions: 30 December 2024 | Viewed by 252
Special Issue Editors
2. Department of Geotechnical Engineering, Tongji University, Shanghai 200092, China
Interests: tunnel engineering; numerical modeling in geotechnical engineering; vulnerability assessment; probabilistic risk analysis; resilience engineering
Special Issues, Collections and Topics in MDPI journals
Interests: data fusion; computer vision; underground space; tunneling; rock engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Infrastructure, including buildings, bridges, rail transit, pipelines, and utility tunnels, are essential components of modern societies. Ensuring the reliability, managing risks, and enhancing the resilience of these critical infrastructures are thus of paramount importance. This Special Issue aims to provide a platform for researchers, practitioners, and experts to share their research findings, methodologies, and case studies on the utilization of advanced artificial intelligence (AI) techniques and mathematical modeling to address reliability, risk, and resilience challenges in various infrastructure systems.
Potential topics include, but are not limited to, the following:
- Predictive maintenance using AI for infrastructure;
- Data driven analytics and Bayesian learning;
- Machine learning and its application;
- Risk assessment and management in infrastructure;
- Resilience optimization in infrastructure;
- Uncertainty quantification in infrastructure systems;
- AI-enhanced decision support for infrastructure planning;
- Simulation-based reliability assessment in infrastructure;
- Deep learning for analyzing urban infrastructure data;
- Multi-agent systems for disaster recovery and emergency response;
- Data-driven approaches for modeling in infrastructure;
- Resilient urban design and planning using mathematical modeling;
- Physics-informed neural network for solid mechanics.
Dr. Zhongkai Huang
Dr. Jiayao Chen
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- infrastructure
- artificial intelligence
- mathematical modeling
- reliability, risk, and resilience
- earthquake, flood, fire, typhoon, surcharge, excavation, etc.
- multiscale analysis
- damage analysis and assessment
- numerical modeling
- risk assessment models
- resilience assessment
- machine learning
- physics-informed neural network
