CAJ | 학술논문

　　为提高教学质量评价准确性，提出一种基于层次分析法和神经网络相融合的教学质量评价方法（AHP-BPNN）。采用层次分析法构建评价指标体系，筛选出对评价结果有重要影响的指标作为BP神经网络输入，采用神经网络建立教学质量评价模型。仿真结果表明，AHP-BPNN不仅简化神经网络的结构，而且提高了教学质量的评价精度和评价效率，是一种可行、有效的教学质量评价方法。
　　위제고교학질량평개준학성，제출일충기우층차분석법화신경망락상융합적교학질량평개방법（AHP-BPNN）。채용층차분석법구건평개지표체계，사선출대평개결과유중요영향적지표작위BP신경망락수입，채용신경망락건립교학질량평개모형。방진결과표명，AHP-BPNN불부간화신경망락적결구，이차제고료교학질량적평개정도화평개효솔，시일충가행、유효적교학질량평개방법。
In order to improve the evaluation accuracy of teaching quality, this paper proposes a teaching quality evaluation method based on analytic hierarchy method and neural network. AHP is used to build the evaluation index system, it selects the important evaluation index as the input of BP neural network. The neural network is used to establish the teaching quality evalu-ation model. The simulation results show that the proposed method can not only simplify the structure of neural network, bu also improve the evaluation accuracy and evaluation efficiency of teaching quality, it is a feasible, effective teaching quality evalua-tion method.