Genetic Algorithm Optimized Neural Network Program

This is a MATLAB-based program that implements neural network optimization using genetic algorithms. The program utilizes genetic algorithms to optimize neural network parameters, enhancing both performance and accuracy. Through iterative genetic algorithm processes, the code systematically improves neural network weights and biases to achieve better fitting with training data. The genetic algorithm mimics biological evolution by simulating natural selection, crossover, and mutation operations to find optimal solutions. This implementation features key MATLAB functions such as population initialization, fitness evaluation using neural network error metrics, crossover operations for parameter recombination, and mutation mechanisms to maintain genetic diversity. The program helps researchers and engineers better understand and apply neural networks, enabling improved results across various application domains by combining evolutionary computation with neural network training.