Evaluation Model and Simulation of Basketball Teaching Quality Based on Maximum Entropy Neural Network
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12C) 873-877
Department of sports training and competition, Shandong Sport University, Jinan 250102, China
Establishment and implementation of models of teaching quality evaluation are important tasks for teaching management in colleges. In this thesis, we use a neural network (NN) model optimized by maximum entropy principle, conduct fitting for complicated nonlinear relationship between many indices and evaluation results to evaluate basketball teaching quality, and implement simulated residual comparison with back propagation (BP) NN model that has not been optimized. Results demonstrate that the evaluation results of maximum entropy NN model are better than those of the BP NN model that has not been optimized in experimental function simulation and example verification, thereby indicating that the optimized model has strong generalization ability and high degree of confidence. This optimization algorithm is feasible in establishing evaluation models for basketball teaching quality.