Intelligent Data Analysis for Multidisciplinary Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (20 February 2025) | Viewed by 343
Special Issue Editor
Special Issue Information
Dear Colleagues,
This Special Issue is dedicated to exploring the vast potential of intelligent data analysis across multiple disciplines. While the significance of intelligent data analysis, powered by advanced analytic techniques, machine learning, and artificial intelligence, has been well established in recent years, harnessing its full potential in multidisciplinary settings remains a challenge. Such settings require domain-specific knowledge and often face cross-disciplinary hurdles, including communication barriers, coordination issues, and differing objectives and evaluation approaches, which complicate the solution process.
In this Special Issue, we aim to research the value that lies in applying intelligent data analysis techniques to a variety of fields, including healthcare, environmental science, logistics, social sciences, and more. We particularly welcome contributions that demonstrate the application of intelligent data analysis techniques to address the unique characteristics of specific domains.
While the focus of this Special Issue is on application, we believe that this topic needs to be approached from multiple perspectives. We invite theoretical papers that provide foundational insights and review articles that offer comprehensive overviews of the field. Additionally, application-oriented papers that utilize intelligent data analysis techniques to solve real-world problems, demonstrating practical implementations and solutions, are highly encouraged. Finally, research papers presenting novel solution procedures, innovative methodologies, and new approaches tailored to multidisciplinary applications are highly valued.
Prof. Dr. Frank Klawonn
Guest Editor
Manuscript Submission Information
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Keywords
- analytics
- data mining
- machine learning
- artificial intelligence
- real-world data
- multidisciplinary integration
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