Particle Swarm Optimization for Enhanced BP Neural Network in Fault Diagnosis

This algorithm presents an improved particle swarm optimization (PSO) method for optimizing backpropagation (BP) neural networks, specifically designed for fault diagnosis in cascaded frequency converters. It includes both conventional BP neural network implementations and the enhanced PSO-BP neural network approach, featuring comparative analysis with example datasets to demonstrate superior diagnostic performance. Key code components involve PSO population initialization, velocity updating mechanisms, and neural network weight optimization procedures.