SVM with Genetic Algorithm Optimization for C and G Parameters
MATLAB implementation of SVM utilizing genetic operators for optimized parameter selection of C and G parameters.
Genetic Algorithm-Based PID Tuning
This MATLAB program implements PID controller tuning using genetic algorithms for parameter optimization. The approach provides an efficient global optimization method that requires no initial parameter information and can find globally optimal solutions through evolutionary computation techniques.
Parameter Optimization for libsvm
A parameter optimization program for libsvm that provides full grid search optimization specifically designed for SVR (Support Vector Regression), primarily used for SVM regression prediction with detailed implementation of parameter tuning algorithms and cross-validation techniques.
PSO-SVM: Parameter Optimization for Support Vector Machines
Implements parameter optimization for support Vector Machines using computational algorithms to enhance model performance
Transformer Fault Prediction Using Machine Learning
A comprehensive framework for transformer fault prediction involving data preparation, preprocessing, parameter optimization, and intelligent anomaly detection
MATLAB Implementation of LIBSVM Parameter Optimization
MATLAB code implementation for LIBSVM parameter tuning with enhanced algorithm explanations