Fuzzy C-Means Algorithm Prone to Local Optima Convergence and Genetic Algorithm Enhancement

The Fuzzy C-Means (FCM) algorithm often converges to local minima. To overcome this limitation, we integrate genetic algorithm optimization with FCM clustering. The genetic algorithm determines optimal initial cluster centers through iterative evolution operations, after which standard FCM clustering produces improved classification results with enhanced stability and accuracy.

Training Artificial Neural Network Systems: Local Minima Issues in TRAINBP Algorithm

The TRAINBP algorithm for training artificial neural network systems suffers from limitations such as local minima and slow convergence rates, along with improved BP algorithm implementation strategies.