Explore MATLAB source code curated for "自适应遗传算法" with clean implementations, documentation, and examples.
This program implements image enhancement through an adaptive genetic algorithm, with core concepts derived from a research paper published in the "Chinese Journal of Computers". The implementation includes population initialization, fitness evaluation based on image quality metrics, and adaptive crossover/mutation operations.
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MATLAB source code for adaptive genetic algorithm utilizing Gram-Schmidt orthogonalization decomposition. Users can alternatively implement QR decomposition for potential code simplification and computational efficiency improvements.
The adaptive genetic algorithm achieves high computational speed but tends to suffer from premature convergence. This program effectively addresses this issue through dynamic parameter adjustment and fitness-based operator adaptation.
This MATLAB code implements an adaptive genetic algorithm that addresses the common issue of premature convergence. While adaptive GA offers faster convergence speeds, the implementation includes a premature convergence detection flag and threshold mechanism to maintain solution diversity and prevent stagnation in local optima.
MATLAB-coded adaptive genetic algorithm featuring self-adjusting crossover and mutation probabilities based on fitness values, dynamically optimizing these parameters relative to optimal solutions
MATLAB Code Implementation of Adaptive Genetic Algorithm with Dynamic Probability Adjustment
MATLAB code implementation of adaptive genetic algorithm featuring dynamic crossover and mutation probability adjustments
MATLAB Implementation of Adaptive Genetic Algorithm with Code-Level Descriptions