Special Issue "Challenges in Civil and Earthquake Engineering Addressed by Data-Driven/AI Approaches"
A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".
Deadline for manuscript submissions: 31 May 2023 | Viewed by 1164
Special Issue Editors

Interests: numerical modelling of ground motion records; probabilistic and deterministic seismic hazard analysis; nonlinear time history analysis; seismic vulnerability and risk analysis

Interests: structural health monitoring; earthquake engineering; seismic safety; and vulnerability assessment; AI/data driven methods

Interests: structural health monitoring; earthquake engineering; seismic safety; and vulnerability assessment; risk analysis; and reliability-based analysis
Special Issue Information
Dear Colleagues,
We are delighted to announce that Doctor Shaghayegh Karimzadeh will serve as the leading guest editor, in collaboration with Doctor Onur Kaplan and Doctor Vasco Bernardo as the co-editors, for a Special Issue of our journal that will be devoted to the application of Data-driven (DD), Machine Learning (ML) and Artificial Intelligence (AI) techniques to problems in civil and earthquake engineering. In recent years, DD/ML/AI approaches have proliferated, with the potential to drastically alter and enhance the role of data science in a variety of fields, including civil and earthquake engineering challenges. The Special Issue's emphasis is on applying more-advanced DD, ML and AI approaches to various civil engineering challenges and real-world problems, including those involving earthquake engineering, structural engineering, seismology, geotechnical and geophysical engineering. Moreover, this Special Issue aims to improve the transferability of research findings, the quality of data generation, sharing, and collection, the quality of the literature used to validate and compare models, and the process of identifying future work.
The following topics are of interest to this Special Issue but are not limited to:
- DD/ML/AI-based approaches in structural engineering, seismology, geotechnics, and geophysics
- Structural health monitoring applications
- Vibration analysis on buildings
- Numerical modelling of civil engineering structures
- Data-driven approaches for seismic vulnerability and risk assessment
- Risk mitigation and disaster management studies
- Big data analysis for signal processing and microzonation studies
- Ground motion modelling and simulation
- Multi-hazard assessment, seismic safety and urban resilience studies
- Performance-based design and assessment of civil engineering structures
- Resilience-based design of civil engineering structures
- Optimization of numerical approaches for seismic assessment
- Seismic isolation
Dr. Shaghayegh Karimzadeh
Dr. Onur Kaplan
Dr. Vasco Bernardo
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. Buildings is an international peer-reviewed open access monthly 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 2000 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
- machine learning approaches
- artificial intelligence and data-driven
- earthquake engineering
- seismic safety assessment
- risk analysis
- ground motion modelling
- multi-hazard assessment
- structural health monitoring
- resilience studies
- performance-based design and assessment