Enhancing public art communication through emotional intelligence based on type-2 fractional fuzzy sets
Abstract Emotional intelligence (EI) is effective ways for understanding others' emotions and communicating with empathy. It is apparent that EI is filled with ambiguity as well as uncertainty because of its immediate connection to humans. To handle such type of amplification, this research stu...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-08-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-025-01210-w |
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| Summary: | Abstract Emotional intelligence (EI) is effective ways for understanding others' emotions and communicating with empathy. It is apparent that EI is filled with ambiguity as well as uncertainty because of its immediate connection to humans. To handle such type of amplification, this research study introduces an advanced version of the fuzzy set, called the type-2 fractional fuzzy set (T2FFS), that allows decision makers to better formalize their judgments. A T2FFS has two components: a primary membership and a secondary membership. The primary membership indicates the truth degree of judgment, and the secondary membership further indicates the reliability degree of the truth. Some basic operational laws and certain aggregation operators are defined to deal easily with the decision-making problem under T2FFSs on the basis of Schweizer-Sklar norms. We developed some strong mathematical techniques utilizing two separate theories of Schweizer-Sklar power aggregation models and operators. To demonstrate the superiority and efficiency of newly developed theories, novel TOPSIS and WASPAS methods are discussed. Further, the proposed method is applied to numerical examples related to emotional intelligence in detail. Additionally, a comparative study presented that how well derived aggregation works with earlier mathematical techniques. |
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| ISSN: | 2196-1115 |