Fuzzy Logic in Artificial Intelligence Systems
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Fuzzy Sets, Systems and Decision Making".
Deadline for manuscript submissions: 31 May 2024 | Viewed by 7429
Special Issue Editor
Interests: fuzzy logic; machine learning; evolutionary algorithms; computational intelligence; information theory
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The capability to learn from data is a proper feature of machine learning (ML). MLs are based on the idea that systems can learn from data whether suitably trained. However, such systems do not provide the expected results because the degree of knowledge is poor or even missing. For designing suitable artificial intelligent systems, either learning and knowledge are needed. Thus, the task of fuzzy logic is to add knowledge to the systems for improving their performances. The combination between knowledge and learning has given rise to the design of hybrid intelligent systems. The optimization of this kind of systems is also based on nature-inspired optimization algorithms. Therefore, ML nature-inspired systems can be enhanced by adding fuzzy techniques. This Special Issue provides a platform for researchers from academia and industry to present their novel and unpublished works in the domain of intelligent control, robotics, intelligent transportation systems, pattern recognition, medical diagnosis, decision systems, and optimization of complex problems.
Dr. Danilo Pelusi
Guest Editor
Manuscript Submission Information
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Keywords
- fuzzy controllers
- neuro-fuzzy systems
- soft computing
- fuzzy-evolutionary systems
- pattern recognition
- intelligent health systems
- expert systems
- intelligent agents
- machine learning
- intelligent transportation systems
- data mining
- intelligent optimization
- decision systems