Enumeration Method
Optimization Based on Enumeration Algorithm
Genetic Algorithm Optimization for BP Neural Networks
Implementation of genetic algorithm-optimized BP neural network featuring a three-layer network architecture and elite preservation strategy for enhanced convergence
Five-Degree-of-Freedom Vehicle Model
The five-degree-of-freedom vehicle model is widely used by suspension research institutions and scientific organizations for suspension optimization using various software tools. MATLAB has become increasingly prevalent and plays a crucial role in vehicle dynamics research. Vehicle vibration dynamics simulation and analysis extensively utilize MATLAB/Simulink modules, where researchers can implement mathematical models using differential equations, transfer functions, or state-space representations to simulate vertical, pitch, and roll motions.
Optimization of RBF Networks Using Particle Swarm and Genetic Algorithms
Implementation of RBF network optimization using Particle Swarm Optimization and Genetic Algorithms, featuring comparative analysis with code-based methodology descriptions
Time Series Prediction Using Neural Networks Optimized with Genetic Algorithm
Implementation of genetic algorithm-optimized neural networks for time series prediction. The genetic.m interface function provides straightforward configuration, allowing direct modification of neural network parameters. Users can easily substitute their own data files by updating the load function call, enabling efficient adaptation to diverse datasets.
PSO Algorithm for Optimizing PID Parameter Tuning
Implementation of a Particle Swarm Optimization (PSO) algorithm for PID parameter optimization, achieving significant performance improvements in control systems
Supervised Feature Selection and Optimization with MATLAB Implementation
MATLAB implementation of supervised feature selection and optimization based on least squares algorithm, including test datasets and comprehensive code documentation with technical specifications
Optimizing Weights and Thresholds of BP Neural Networks Using Traditional Genetic Algorithm
Traditional Genetic Algorithm optimizes weight and threshold parameters in BP neural networks, achieving improved convergence characteristics through evolutionary computation techniques.
Particle Swarm Optimization Combined with Continuation Power Flow Method
This hybrid approach combines Particle Swarm Optimization and Continuation Power Flow method to optimize transformer tap settings through multi-variable optimization, significantly enhancing system stability through coordinated parameter adjustments.
Particle Swarm Optimization (PSO) for Support Vector Machine (SVM) Parameter Tuning
Using Particle Swarm Optimization (PSO) to optimize Support Vector Machine (SVM) parameters -c and -g with implementation insights