TS Fuzzy Neural Network

The TS fuzzy neural network program is an algorithm designed for comparative analysis of output data, network mean squared error evaluation, and membership function comparison. This implementation typically involves coding the fuzzy inference system using MATLAB's Fuzzy Logic Toolbox or similar frameworks, where key components include fuzzy rule base construction, antecedent parameter tuning, and consequent linear function optimization. The program enables performance assessment by comparing output results across different datasets, evaluating network efficiency through mean squared error calculations, and verifying the accuracy of membership functions. This design approach assists researchers and engineers in better understanding fuzzy neural network mechanisms through practical code implementation, facilitating network performance optimization and accuracy improvement. By utilizing the TS fuzzy neural network program with proper parameter initialization and gradient-based learning algorithms, users can gain deeper insights into system behavior and enhance adaptability for various application scenarios.