Study on Undergraduate Teaching Job Quality Assessment Based on Artificial Fish-BP Neural Network

Lihua Li, Fuming Liu, Chang-long Wang
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Abstract

In order to comprehensively evaluate the undergraduate teaching job quality of colleges and universities, the evaluation simulation model was set up using artificial fish-swarm-neural network; taking the teaching management ,major construction and curriculum reform, teaching research and the results , the teaching quality for the input layer, the undergraduate theory teaching job quality of colleges and universities for the output layer, establishing artificial neural network model and training and testing for the network using actual data. Practice shows that the model has better recognition accuracy. Finally, the assessment results digitized came to the conclusion that can be accurately, intuitively reflect the merits of the undergraduate theory teaching job quality, thus demonstrating that the artificial fish-BP neural network has broad prospects the evaluation at the undergraduate theory teaching job quality of colleges and universities.
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基于人工鱼- bp神经网络的本科教学工作质量评价研究
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