Abstract
To improve the accuracy of teaching quality assessment, an assessment model based on analytic hierarchy process (AHP) and learning vector quantization (LVQ) neural network is proposed in this paper. First a hierarchical model of teaching quality assessment was built by AHP. Then the weight of each assessment index was defined. All the indices involved were put into an LVQ neural network. The neural network model was trained and its generalization ability was also tested. The simulation result shows that compared with a traditional BP neural network, an AHP-LVQ network has simpler structure, better learning ability, faster convergence rate, higher assessment accuracy as well as better generalization ability.
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Acknowledgements
The research work was supported by Social Science Foundation of Liaoning Provincial under Grant No. L14CYY022.
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Hu, S., Gu, Y., Jiang, H. (2015). Teaching Quality Assessment Model Based on Analytic Hierarchy Process and LVQ Neural Network. In: Huang, Z., Sun, X., Luo, J., Wang, J. (eds) Cloud Computing and Security. ICCCS 2015. Lecture Notes in Computer Science(), vol 9483. Springer, Cham. https://doi.org/10.1007/978-3-319-27051-7_42
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DOI: https://doi.org/10.1007/978-3-319-27051-7_42
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