Explore MATLAB source code curated for "预测" with clean implementations, documentation, and examples.
Neural networks excel in nonlinear mapping capabilities. This implementation uses Elman recurrent neural networks for SSE opening price prediction with demonstrated efficiency and accuracy, featuring sliding window data preprocessing and backpropagation through time training.
Time series forecasting holds significant importance in economics and engineering fields. This study leverages the characteristics of dynamic neural networks to propose a time series prediction methodology, implementing a designed dynamic network to forecast response time series of Duffing's equation. Results demonstrate that dynamic neural networks effectively predict response time series of dynamic systems, with MATLAB implementation utilizing NARX (Nonlinear Autoregressive with Exogenous Input) network architecture and time-delay feedback mechanisms.
Implementation of Bat Algorithm-Optimized Relevance Vector Machine for Accurate Data Modeling and Prediction
The wine dataset originates from the UCI repository and contains chemical analysis results of three different wine cultivars from the same region in Italy. The dataset comprises 178 samples, each with 13 feature components (chemical properties), along with predefined class labels. We allocate 50% of the samples (89 instances) as the training set and the remaining 50% as the test set. By training an SVM classifier on the training data, we generate a classification model that can predict class labels for the test set. The implementation typically involves feature scaling, model training with kernel selection, and performance evaluation using metrics like accuracy.
This implementation of Francis R. Bach's Bolasso algorithm provides robust feature selection and predictive modeling capabilities for high-dimensional problems. The algorithm leverages bootstrap sampling with regularization regression techniques, utilizing Karl Skoglund's lars (least angle regression) implementation for efficient coefficient path computation and feature ranking.
Implementation of Multilayer Perceptron (MLP) trained with Backpropagation, Radial Basis Function Network (RBF Network), and Support Vector Machine (SVM) for regression and prediction tasks on 2D function datasets including Mexican Hat, Gabor, Friedman, and Polynomial functions
A MATLAB implementation of BP neural network for predicting various types of data with detailed code structure and algorithm explanations
Source code for seven radial basis function artificial neural networks, including implementations for pattern classification and prediction with algorithmic enhancements
SVM Neural Network for Data Classification and Prediction - Wine Variety Identification with Implementation Insights
A self-developed MATLAB routine for chaotic time series prediction, featuring practical implementation approaches and detailed code explanations.