Explore MATLAB source code curated for "预测" with clean implementations, documentation, and examples.
Wavelet Neural Networks for short-term power load forecasting, including wavelet processing programs and neural network implementations, with normalized input data for accurate predictions
Implementation of time series forecasting through wavelet neural networks with four MATLAB m-files demonstrating the complete prediction model architecture
A comprehensive comparison between Kalman Filter and Wiener Filter for filtering and prediction of first-order Gaussian-Markov processes, including code implementation considerations and algorithm characteristics.
Custom-implemented least squares support vector machine prediction model with runnable code, seeking performance improvements and enhanced predictive capabilities.
Utilizing Support Vector Machine models to predict water eutrophication influencing factors, supplemented by multivariate regression analysis for comprehensive condition forecasting, including algorithm implementation approaches and key function descriptions.
The Levinson-Durbin Algorithm for Linear Predictive Control in Speech Processing and Spectral Envelope Estimation
Comparative analysis of BP neural network approaches for wind power prediction with and without NWP (Numerical Weather Prediction) data, including implementation datasets and practical case studies
Time series prediction using neural networks demonstrated through sunspot data and rotor fault signal analysis, featuring MATLAB programming approaches including data preprocessing, network architecture selection, and prediction accuracy evaluation
Stock Market Nonlinear Analysis and Prediction Toolbox integrates the original nonlinear time series analysis toolbox programs, featuring multiple complexity analysis methods (such as Higuchi's method, box-counting method), phase space reconstruction techniques (Cao's method, GP algorithm, mutual information method), maximum Lyapunov exponent determination (Wolf's method, small data sets method) and prediction procedures (Lyapunov exponent method, one-step multi-step prediction, etc.). The toolbox demonstrates high execution efficiency and practical usability, with optimized algorithms for real-world financial data processing.
Implementation of RBF Network Prediction Based on Clustering Algorithm using MATLAB Programming Language