BP Neural Network Universal Prediction Tool

This Chinese-developed universal BP neural network prediction program is compatible with MATLAB 2009 and later versions, featuring direct data input functionality. The program implements a neural network model based on the backpropagation algorithm, capable of training on input data and generating predictions. It utilizes key MATLAB functions like 'newff' for network creation, 'train' for model training, and 'sim' for prediction generation. The tool finds applications across multiple domains including finance, healthcare, and engineering, assisting users in data analysis and forecasting tasks. The implementation handles both large-scale and small-scale datasets efficiently through optimized matrix operations and customizable network parameters (hidden layers, learning rate, epochs). The algorithm employs gradient descent optimization with momentum to enhance convergence speed and prediction accuracy. The program features a user-friendly interface that simplifies operation through intuitive parameter configuration panels and visualization of training progress. Key components include data normalization preprocessing, automatic network architecture selection, and performance metrics calculation (MSE, R-squared). If you're seeking a robust yet straightforward prediction tool, this BP neural network universal prediction program serves as an ideal choice for various predictive modeling scenarios.