Special Issue "Artificial Intelligence in Infrastructure Geotechnics"
A special issue of Infrastructures (ISSN 2412-3811).
Deadline for manuscript submissions: 30 September 2022 | Viewed by 2862
Interests: geotechnical engineering; soil improvement; soft soils; slopes stability; soft computing; data mining; Artificial Intelligence
Interests: machine learning, reliability; earthquake engineering; pile foundation; site characterization
Special Issues, Collections and Topics in MDPI journals
Infrastructure geotechnics play a key role in countries’ development, being present on all basic infrastructures, including transportations, water supply, sewers, electrical grids, or telecommunications. Complex geotechnical problems are regularly faced when dealing with these infrastructure projects, for which traditional methods are unable to give the most adequate answer. Alternatively, artificial intelligence techniques are being largely applied in different infrastructure geotechnics problems due to its promising potential to solve high non-linear and complex problems. In fact, in recent decades, there has been a trend to promote interdisciplinary research, where one field poses interesting problems and data, and the other field provides the problem-solving tools (i.e., methods and algorithms).
In this Special Issue, we solicit high-quality original research articles focused on how complex infrastructure geotechnics problems are being solved with the contribution of advanced artificial intelligent algorithms, whether in design or construction, covering the different infrastructure types (e.g., roads, railways, bridges, tunnels, water supply, sewers, electrical grids, telecommunications). We welcome both theoretical and application papers of high technical standard across various disciplines, thus facilitating an awareness of techniques and methods in one area that may be applicable to other areas. We seek high-quality submissions of original research articles as well as review articles on all aspects related to infrastructure geotechnics that have the potential for practical application.
Topics of interest include but are not limited to:
- Tunnels and deep excavations;
- Asset management;
- New construction materials and mixture design;
- Intelligent constructions;
- Materials behavior (rock, soil, cementitious mixtures);
- Site characterization;
- Soil improvement;
- Monitoring, surveillance, and field measurement methods;
- Virtual reality and augmented reality;
- Advanced design techniques.
Dr. Joaquim Tinoco
Dr. Pijush Samui
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. Infrastructures 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 1600 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.
- infrastructures geotechnics
- water supply
- electrical grids
- artificial intelligence
- machine learning
- artificial neural networks