A Fuzzy Logic Framework for Text-Based Incident Prioritization: Mathematical Modeling and Case Study Evaluation
Incident prioritization is a critical task in enterprise environments, where textual descriptions of service disruptions often contain vague or ambiguous language. Traditional machine learning models, while effective in rigid classification, struggle to interpret the linguistic uncertainty inherent...
Saved in:
| Main Authors: | Arturo Peralta, José A. Olivas, Pedro Navarro-Illana |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/12/2014 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Hybrid Mathematical Framework for Dynamic Incident Prioritization Using Fuzzy Q-Learning and Text Analytics
by: Arturo Peralta, et al.
Published: (2025-06-01) -
Intelligent Incident Management Leveraging Artificial Intelligence, Knowledge Engineering, and Mathematical Models in Enterprise Operations
by: Arturo Peralta, et al.
Published: (2025-03-01) -
Fuzzy Epistemic Logic: Fuzzy Logic of Doxastic Attitudes
by: Jinjin Zhang, et al.
Published: (2025-03-01) -
Fuzzy Logic Concepts, Developments and Implementation
by: Reza Saatchi
Published: (2024-10-01) -
Strategic Human Capital Management in Engineering Workplaces: A Fuzzy Logic-Based Decision Framework
by: Belen Maria Moreno-Cabezali
Published: (2025-01-01)