Explore MATLAB source code curated for "优化" with clean implementations, documentation, and examples.
Implementation of particle position and velocity updates in multi-objective particle swarm optimization, featuring test function simulations and result optimization strategies with code-based parameter adjustments.
MATLAB-based implementation of genetic algorithm for optimizing neural network weights with enhanced code-level descriptions
Reposted source code demonstrating initialization function implementation for genetic algorithm-optimized BP neural networks, featuring population generation and weight initialization techniques.
Multi-Objective Particle Swarm Optimization Algorithm implements the particle swarm optimization principle to simultaneously optimize two objective functions with enhanced convergence mechanisms.
MATLAB M-file implementation of PSO (Particle Swarm Optimization) algorithm for neural network optimization, featuring complete code structure and parameter configuration
This program utilizes genetic algorithms to optimize artificial neural networks for predicting SARS trend variations, implementing evolutionary computation techniques to enhance neural network performance.
This program effectively models the constraints and optimization of distributed generation output with relatively few iteration cycles
This MATLAB implementation of the Adaboost algorithm for license plate training and detection offers robust functionality, though training time may be extensive. The code leverages Adaboost's ensemble learning approach with weak classifiers to create a strong plate detector through iterative weight adjustments and feature selection.
Application of the conjugate gradient method for synthesizing and optimizing cross-coupled resonator filters, with reference to the analytical gradient-based optimization technique presented in Smain Amari's paper "Synthesis of Cross-coupled Resonator Filters Using an Analytical Gradient-Based Optimization Technique."
MATLAB implementation of genetic algorithm optimized backpropagation neural network with clear annotations, ensuring beginners can comprehend the code after understanding the underlying principles