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Journals
Information
Special Issues
Machine Intelligence in Interdisciplinary Areas
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Machine Intelligence in Interdisciplinary Areas

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".

Deadline for manuscript submissions: closed (30 December 2023) | Viewed by 2551

Special Issue Editors

Prof. Dr. Jung-Sup Um

E-Mail Website
Guest Editor
Department of Geography, Kyungpook National University, Daegu 41566, Republic of Korea
Interests: cyber-physical system; remote sensing; geographic information system; designing of special information system
Special Issues, Collections and Topics in MDPI journals
Dr. Tanupriya Choudhury

E-Mail Website
Guest Editor
School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun 248007, Uttarakhand, India
Interests: data mining; business analytics; soft computing; human computer in-teraction; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will present extended versions of selected papers presented at the 3rd INTERNATIONAL CONFERENCE ON MACHINE INTELLIGENCE & DATA SCIENCE APPLICATIONS (MIDAS – 2022), which will be held on December 07 and 08, 2022, at the University of Versailles – Paris Saclay, France. MIDAS-2022 aims to promote and provide a platform for researchers, academia and practitioners to meet and exchange ideas on recent theoretical and applied Machine and Artificial Intelligence and Data Sciences research. The conference targets the theme of Machine Intelligence and its Applications. A wide range of work with comprehensive information on image processing, natural language processing, computer vision, sentiment analysis, voice and gesture analysis, and other topics are invited to the conference. The latest work in multidisciplinary applications such as legal, healthcare, smart society, cyber physical systems, and smart agriculture, among others, are also invited. The conference will be of interest to computer science engineers, machine intelligence lecturers/researchers, and engineering graduates. The conference program consists of wide range of sessions including distinguished lectures, paper presentations and poster presentations, along with prominent keynote speakers and industrial workshops. The theme for the conference is apt in the present scenario, as the world is driven by data and human interference is being limited by the use of various AI technologies. Authors of invited papers should be aware that the final submitted manuscript must provide a minimum of 50% new content and not exceed 30% copy/paste from the proceedings paper.

Prof. Dr. Jung-Sup Um
Dr. Tanupriya Choudhury
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. Information 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.

Keywords

  • geo-sciences and ML applications
  • BCI
  • AI in legal
  • AI in healthcare and medicine
  • smart society
  • smart farming
  • cyber physical system
  • robotics
  • soft computing
  • evolutionary computing
  • predictive analysis

Published Papers (1 paper)

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Research

16 pages, 760 KiB  
Article
Using Genetic Algorithms to Improve Airport Pavement Structural Condition Assessment: Code Development and Case Study
by Alessia Donato and David Carfì
Information 2023, 14(5), 286; https://doi.org/10.3390/info14050286 - 11 May 2023
Viewed by 1286
Abstract
In this paper, we propose a new method of optimization based on genetic algorithms using the MATLAB toolbox “Global Optimization”. The algorithm finds layers moduli of a flexible pavement through the measurement of pavement surface deflections under assigned load conditions. First, the algorithm [...] Read more.
In this paper, we propose a new method of optimization based on genetic algorithms using the MATLAB toolbox “Global Optimization”. The algorithm finds layers moduli of a flexible pavement through the measurement of pavement surface deflections under assigned load conditions. First, the algorithm for the forward calculation is validated, then the algorithm for the back-calculation is proposed, and the results are compared, in the case of airport pavements, with other software using different back-calculation techniques. The goodness of the procedure and the way of managing the algorithm operator is demonstrated by means of positive feedback obtained from the comparison of the results of ELMOD and BackGenetic3D. Moreover, the findings of the analysis prove that, in such an optimization procedure by GA, the best solution is always reached with a low number of generations, generally less than 10, allowing a reduction in the time of calculation and choosing a population big enough to select with good probability, in the initial population, solutions close to the real ones. The code is made available in such a way that the reader can easily apply it to other flexible pavements in the case of fully bonded layers (both for roads and airports). In particular, interested readers can easily modify the algorithm parameters (population number, stop criteria, probability of mutation, cross-over, and reproduction) and the type of fitness function to minimize, together with the geometric and load characteristics (number and thickness of the layers and the range of module variation). The possibility to change the algorithm parameters and the fitness function allows for exploring different scenarios in order to find the best solution in terms of fitness values. It is also possible to intervene in the time of calculation by managing the algorithm’s stopping criteria. Full article
(This article belongs to the Special Issue Machine Intelligence in Interdisciplinary Areas)
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