The teaching work is the center work of the school, and the teaching quantity evaluation is the core and base of teaching evaluation. The teaching quantity evaluation plays an important role in the process of promoting the healthy development of school teaching work and improving the teaching quality. This thesis expounds the design and implementation of artificial neural network applied in teaching quality evaluation, and builds the modal of artificial neural network applied in teaching quality evaluation by introducing and analyzing the traditional teaching quality evaluation. According to the examples to evaluate and analyze the model, application of BP neural network in teaching quality evaluation is proved to be feasible. This model possesses strong functions of study association and fault tolerance, moreover both its analysis results and process approach the metal process and analysis method of human brain, which greatly improves the accuracy for teaching quality evaluation.
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