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Implementations of fuzzy logic and neural network algorithms, often in MATLAB or Python.

Mathematical framework of the Regularized Fuzzy Neural Network. How the system simplifies its own rules to save resources. Experimental Results RK rar

Summary of how regularization improves fuzzy system accuracy. RK rar

2. Core Technical Concept: Regularized Fuzzy Neural Networks (RFNN) RK rar

Uses mathematical penalties (like L1 or L2 regularization) to ensure the model performs well on new, unseen data rather than just "memorizing" training data.

The report inside such a file focuses on improving . A Fuzzy Neural Network combines the human-like reasoning of fuzzy logic with the learning capabilities of neural networks. The "Regularized" aspect is the primary innovation, which: