Statistical Modeling and Data-Driven Methods in Aviation Systems
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".
Deadline for manuscript submissions: 30 September 2024 | Viewed by 1419
Special Issue Editor
Interests: statistical process modeling and simulation; aviation applications of Bayesian inference; acquisition and analysis of distributed transportation data
Special Issue Information
Dear Colleagues,
Statistical modeling is an interdisciplinary subject involving, among other topics, probability theory, statistics, approximation theory, optimization, and computation. It focuses on the development of computer models that accurately translate the operation of real-world processes into algorithms that may be executed by computing devices to provide designers and analysts with information on the operational details of those processes. That information, in turn, allows these individuals to properly optimize processes that can produce the desired results. Valid simulation models based upon measurable data, often collected from widely disparate and distributed sources, are key to minimizing implementation costs, optimizing desired output parameters, and maximizing quality and safety in aviation systems.
The main focus of this Special Issue is the progress of the development and implementation of statistical modeling and machine learning methods in the design and analysis of aviation systems. Such systems can be related to areas such as air traffic management, baggage handling, passenger security, and enhancement of quality and safety in air transportation. Our goal is to facilitate communication on current research and the translation of those research developments into practical applications and tools. We welcome scholars to submit research related to the theory that underlies all forms of statistical modeling and data analysis in order to apply it to aviation systems, and to practical applications thereof. Topics of interest include, but are not limited to, new machine learning methods, statistical methodology, pattern recognition as applied to air vehicle recognition, optimization techniques for air traffic management, advances in computational aspects of simulation, and acquisition and analysis of distributed system data.
Dr. John H. Mott
Guest Editor
Manuscript Submission Information
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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
- artificial intelligence
- big data and analysis
- machine learning
- deep learning
- pattern recognition
- computer vision
- data mining
- statistical modeling applications
- air traffic systems modeling
