Entropy for Machine Learning and Complex Systems Toward Regional Sustainable Development
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".
Deadline for manuscript submissions: closed (15 April 2022) | Viewed by 36332
Special Issue Editors
Interests: machine learning; sustainable development; entropy; decision making methods; operation management; sustainability
Special Issues, Collections and Topics in MDPI journals
Interests: operations research; optimization and decision analysis; multicriteria decision making; multiattribute decision making (MADM); decision support systems; civil engineering; energy; sustainable development; fuzzy sets theory; fuzzy multicriteria decision making; sustainability; management; game theory and economical computing knowledge management
Special Issues, Collections and Topics in MDPI journals
Interests: multi-criteria decision making problems; computational intelligence; sustainability neuro-fuzzy systems; fuzzy; rough and intuitionistic fuzzy set theory; neutrosophic theory
Special Issues, Collections and Topics in MDPI journals
Interests: multi-criteria; fuzzy set; soft computing; renewable energy; sustainability; circular economy; technology assessment; hypersoft sets; sustainable development goals
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent decades, a need has arisen for forecasting and predictive modeling to deliver real-time solutions to sustainable development problems by integrating the models from the rapidly developing fields of machine learning, complex systems, and entropy. Machine learning is an approach for data analysis, which constructs the analytical model by giving computer systems the ability to “learn.” Machine learning is based on the idea that systems can learn from data, identify patterns, and make decisions with minimal human intervention. The concept of entropy originally developed from physics fields, but, it is clear that entropy is deeply related to machine learning and complex systems. Besides applications in machine learning, entropy is a general measure, commonly used for qualitative analysis of complex systems. In this regard, entropy is a powerful descriptive method, which presents an operational and theoretical framework to attain both qualitative and quantitative descriptions of the intrinsic properties of machine learning and complex systems theories. Therefore, to understand the importance of entropy concepts in machine learning and complex systems, in this Special Issue, we are interested in providing state‐of‐the‐art literature of entropy concepts and establishing a reliable connection between machine learning, complex systems, and the sustainable development context.
Dr. Abbas Mardani
Prof. Dr. Edmundas Kazimieras Zavadskas
Dr. Dragan Pamučar
Prof. Dr. Fausto Cavallaro
Guest Editors
Manuscript Submission Information
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Keywords
- entropy
- machine learning
- complex systems
- predictive modeling
- sustainable development
- forecasting
- decision making
- complex systems
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