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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM38377
Volume:
8 |
11 |
Nov 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Neuro-fuzzy systems (NFS) combine the learning capabilities of neural networks with the reasoning and interpretability of fuzzy systems. This paper presents a comparative analysis of recent advances in NFS across various domains, including engineering, construction, medical systems, and robotics. A synthesis of methodologies, application areas, and future challenges is provided. The analysis shows that NFS offers promising results in handling complex, nonlinear problems across multiple fields, with growing applications in healthcare and autonomous systems. This paper also discusses challenges such as computational complexity and integration with deep learning frameworks.
KEYWORDS
Publication Date
2/10/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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