BP network model optimized by adaptive genetic algorithms and the application on quality evaluation for class teaching

A new algorithm with adaptive genetic algorithms and error back propagation (BP) algorithm is proposed in this paper, which performs genetic algorithm global search capability and BP algorithm powerful local-optimization ability. The computational results suggest that the algorithm has powerful ability of solving the problem of quality evaluation for class teaching. The performance of adaptive genetic algorithms is very promising because it is able to find an optimal or near-optimal solution for the test problem and the adaptive genetic algorithms is successful in adjusting the BP neural network connection weights and thresholds.