[Matlab] Based on the particle swarm optimization algorithm to optimize the data regression prediction of BP neural network (Excel can directly replace the data)

1. Model Principle

Optimizing the data regression prediction of BP neural network based on particle swarm optimization algorithm (Particle Swarm Optimization, PSO) is a method that combines PSO and BP neural network to improve the performance of BP neural network in regression prediction tasks. BP neural network is a commonly used forward artificial neural network, which is used to deal with regression and classification problems, but it may fall into a local optimal solution on complex problems. PSO is a global optimization algorithm that can help find better neural network weights and bias values, thereby improving the prediction accuracy of BP neural networks.

The principle of "data regression prediction based on particle swarm optimization algorithm to optimize BP neural network" is introduced below:

1. Introduction to BP neural network :