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Research on Piano Informatization Teaching Strategy Based on Deep Learning

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  • Yihao Hou
  • Naeem Jan

Abstract

Applying information technology to piano teaching can effectively avoid these problems. The application of information teaching means can not only enrich teaching methods but also enhance students’ interest in learning. Deep learning (DL) focuses on immersing students in knowledge and learning situations, emphasizing critical thinking, and realizing the intrinsic value of knowledge. Understanding DL theory is of great significance to deepening the teaching reform in China. BP algorithm is a very effective algorithm for prediction and evaluation. In this paper, the complex factors affecting the quality of piano information teaching are comprehensively considered, and the improved BP neural network (BPNN) algorithm is used to evaluate and predict the quality of piano information teaching. The model structure of BPNN for evaluating and predicting the quality of piano information teaching is given and simulated in MATLAB. The results show that the evaluation and prediction method overcomes the subjective factors of expert evaluation and obtains reasonable results. Compared with the traditional BPNN algorithm, it has good applicability.

Suggested Citation

  • Yihao Hou & Naeem Jan, 2022. "Research on Piano Informatization Teaching Strategy Based on Deep Learning," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-8, March.
  • Handle: RePEc:hin:jnlmpe:5817752
    DOI: 10.1155/2022/5817752
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