Modeling and Analysis of College Teaching Quality Based on Bp Neural Network
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Yuanjing Zhao, Wei Tang
How to improve the teaching quality of higher education has become the focus of current higher education. However, in colleges and universities, classroom teaching is still the main channel to implement education, and its quality to a large extent reflects and determines the quality of education in colleges and universities. Teaching evaluation is a key measure to improve the quality of education and teaching. Therefore, it is particularly important to establish a scientific and reasonable evaluation system for college classroom teaching quality. In the evaluation system of the past, is more directly is adopted to establish the mathematical model of evaluation system, such as the weighted average method, analytic hierarchy process and fuzzy comprehensive evaluation method, etc. all of these methods in the evaluation process requirements affecting factors (namely evaluation index) has a linear relationship between, and it is difficult to rule out all sorts of randomness and subjectivity, easy to cause the evaluation results distortion and bias. As a new technology, artificial neural network (Ann) has been widely used in various evaluation problems due to its characteristics of nonlinear processing, adaptive learning and high fault tolerance. BP network is one of the many types of artificial neural network, and it is a multi-layer feed forward network with strong nonlinear mapping ability.
Bp neural network; Universities; Teaching quality; Evaluation; Optimization