Improving the Convergence of the Genetic Neural Network in the Crystallizing of Sugar Using Q-Learning
Abstract：The crystallizing speed of cane sugar is learned and predicted by the model of feedforward neural network using genetic algorithms. To counter the problem in the model which needs a lot of calculations but has slow speed of convergence, we use Q-learning with reinforcement to decide on the variation probability of genetic algorithms and to increase the convergence speed of learning. The results of the simulation show the effectiveness of the method.
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Publication Date：2001-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 887-890 )