Submission Deadline: 28 February 2025 View: 968 Submit to Special Issue
Prof. S.A. Edalatpanah, Ayandegan Institute of Higher Education, Iran
Prof. Harish Garg, Thapar Institute of Engineering & Technology, India
Real-world data is often uncertain and indeterminate, especially in the big data era. Uncertainty derives from ambiguity, which emerges from a lack of understanding of the processes that produce outcomes. It is essentially subjective; because the environment can only be known through perception and cognition, it will always be viewed as uncertain. Environmental uncertainty is a significant factor producing indeterminacy. There is, however, no direct way to do this; the system works indirectly by influencing the nature of inputs and their effects on other processes within the system. Ambient Intelligence (AmI) and Social Computing (SC) are popular topics fraught with uncertainty and indeterminacy. AmI is a component of a ubiquitous computing environment that allows it to interact with and respond appropriately to people. Also, human-centered computer interface design and ubiquitous computing are the cornerstones of the AmI paradigm, which is based on embedded, customized, context-aware, anticipatory, and adaptive systems and technologies. In addition, social computing is a branch of computer science concerned with the interface between social behavior and computational systems. It utilizes software and technology to build or reproduce social customs and environments. Therefore, blogs, email, instant messaging, social network services, wikis, and bookmarking show social computing concepts. Because decision-makers (DMs) typically cannot estimate a reasonable probability for alternative outcomes, judgments must be made with limited knowledge in uncertain and indeterminate situations. As a result, we need to find ideas that DMs can manage to replace uncertainties and indeterminacies.
Using a fuzzy set is one approach to modeling and quantifying the imprecision and uncertainty inherent in human-centered decision-making. Nevertheless, it cannot address all sorts of uncertain and contradictory data. Hence, the intuitionistic fuzzy set, Picture fuzzy set, Pythagorean fuzzy set, spherical fuzzy set, neutrosophic set, Plithogenic set, and its generalizations have been proposed as extensions of fuzzy sets.
The goal of this special issue is to bring together the most up-to-date research on the methodologies, techniques, and applications of ambient intelligence and social computing, including but not limited to intelligent/smart objects, environments/spaces, and systems under fuzzy set extensions for various practical problems, and to show how researchers have tackled the complex issues that arise from these ideas. We also welcome authors to present state-of-the-art and recent advancements in other soft computing techniques for the mentioned problems.
Potential topics under fuzzy set extensions include but are not limited to the following:
• Pervasive/Ubiquitous Computing and Applications
• Embedded Systems and Software
• Healthcare Systems
• Mobile Computing and Wireless Communications
• Context awareness, social sensing, and inference
• Decision analysis
• Operations Management and Industrial Engineering
• Performance analysis
• Multi-Criteria Decision-Making
• Intelligent and self-organizing transportation networks & services
• Service and Semantic Computing
• Recommender Systems
• Personalization
• User Modeling
• Cognitive Science-Natural Language
• Deep Learning
• Waste management
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