Integrating Neural Networks and Fuzzy Logic: Innovations and Practical Applications
Abstract
The integration of neural networks and fuzzy systems has opened new frontiers in solving complex, real-world problems by combining the adaptive learning capabilities of neural networks with the reasoning power of fuzzy logic. This paper explores advancements in neuro-fuzzy systems, examining their fundamental principles, hybrid architectures, and practical applications across domains such as control systems, decision-making, pattern recognition, and data analytics. By leveraging the strengths of both approaches, neuro-fuzzy systems enable robust, efficient, and intelligent solutions. The study also highlights emerging trends, challenges, and future prospects, emphasizing the transformative potential of this synergistic approach in technology and innovation..
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