A REVIEW OF NEURAL NETWORKS, FUZZY LOGIC, AND NEURO-FUZZY SYSTEMS: FOUNDATIONS, RECENT ADVANCES, AND FUTURE TRENDS

– Neural Networks (NNs) and Fuzzy Logic (FL) are two fundamental paradigms in artificial intelligence that address learning and uncertainty in complex systems [1], [2]. Neural networks demonstrate strong data-driven learning capability [4], [5], whereas fuzzy logic emphasizes interpretability through linguistic rules [2], [7]. However, neural networks often lack transparency [6], and fuzzy logic systems depend on expert knowledge [7]. Hybrid neuro-fuzzy systems, including ANFIS [3], evolving fuzzy systems [20], and deep neuro-fuzzy systems [11], [14], integrate learning and reasoning to overcome these limitations.