Genetic Algorithm Optimized BRF Neural Network

This MATLAB program implements a genetic algorithm-optimized BRF neural network designed for direct prediction tasks. The genetic algorithm mimics biological evolution processes through genetic operations, mutation, and selection mechanisms to search for optimal solutions. The BRF neural network operates based on connections and weights between neurons, where parameter adjustments enhance prediction accuracy. This implementation integrates genetic algorithm optimization with BRF neural networks by tuning network parameters through fitness evaluation, crossover operations, and elite selection strategies. Key MATLAB functions include population initialization, fitness calculation using mean squared error, and weight optimization through iterative generations. The program enables improved prediction performance by evolving optimal network configurations, making it suitable for various forecasting applications. Researchers and practitioners interested in predictive modeling can directly utilize this code for their prediction tasks.