MATLAB Mathematical Modeling Package
MATLAB Mathematical Modeling Package - An Essential Toolkit for Mathematical Modeling Competitions with Advanced Computational Functions
Wheel Pair Analysis Program and Associated Toolkits in MATLAB
MATLAB-based implementation of wheel pair analysis programs and associated toolkits for analyzing train wheel-rail contact relationships, featuring comprehensive contact mechanics simulations and visualization capabilities.
MATLAB-Based Multivariate Linear Regression with Leave-One-Out Cross-Validation Prediction Package
A comprehensive MATLAB package implementing multivariate linear regression analysis with integrated Leave-One-Out Cross-Validation (LOOCV) prediction capabilities, featuring data preprocessing and visualization tools.
Numerical Methods for Partial Differential Equations Package
A comprehensive software package for numerical solutions of partial differential equations, featuring implementations of Lax-Friedrichs, Lax-Wendroff, and upwind schemes with configurable parameters and extensible architecture
SVDD MATLAB Toolbox and Program Suite Including Core and Extended Toolboxes
SVDD's MATLAB toolbox and program collection features both core and extended toolboxes along with a simplified demo program for practical implementation.
Vibration Simulation Using MATLAB and ANSYS
Vibration Simulation with MATLAB and ANSYS - Complete with Program Package and Implementation Examples
Prominent Convex Optimization Packages for International Applications
Internationally Renowned Convex Optimization Packages, Compressed Sensing Theory, and Reconstruction Algorithms with Implementation Insights
Mixed-Integer Nonlinear Programming
A comprehensive package for solving mixed-integer nonlinear programming problems with advanced algorithms and implementation features
Principal Component Analysis Toolkit
Principal Component Analysis Toolkit including source code implementations for both Principal Component Analysis and Independent Component Analysis algorithms.
Using Particle Swarm Optimization to Train Neural Network Parameters
This package implements Particle Swarm Optimization (PSO) for training neural network parameters. Simply run demoPSOnet.m to observe dynamic 2D visualization of the optimization process, where particle positions represent potential neural network weight configurations and their movement reflects the PSO algorithm's search mechanism through solution space.