College of Communication Science and Art, Chengdu University of Technology, Chengdu 610059, China.
Comput Intell Neurosci. 2022 Jul 4;2022:6216232. doi: 10.1155/2022/6216232. eCollection 2022.
The modernization of education necessitates the enhancement of instructional quality. This paper begins with a basic overview of the current state of film and television art education and then goes on to examine the current state of film and television art education and develop a virtual simulation-based teaching mode for film and television art. This paper develops an instructional quality evaluation model to assess the feasibility of this teaching mode. In this model, GA is used to optimize BPNN's initial weights and thresholds, reducing the time it takes BPNN to find the weights and thresholds that satisfy the training termination conditions. Improve BPNN's prediction accuracy and convergence speed in relation to instructional quality evaluation results. The evaluation accuracy of this algorithm can reach 94.31 percent, which is 6.35 percent higher than other methods. Furthermore, the use of virtual simulation technology in the teaching of film and television art in higher education institutions can have a significant impact and have far-reaching research implications. The findings of this study can be used to improve the teaching of film and television art in institutions of higher learning.
教育现代化需要提高教学质量。本文首先对影视艺术教育的现状进行了概述，然后对影视艺术教育的现状进行了考察，并开发了一种基于虚拟仿真的影视艺术教学模式。本文建立了教学质量评价模型，以评估该教学模式的可行性。在该模型中，使用 GA 优化 BPNN 的初始权重和阈值，从而减少 BPNN 找到满足训练终止条件的权重和阈值所需的时间。提高 BPNN 在教学质量评价结果方面的预测准确性和收敛速度。该算法的评估准确率可达 94.31%，比其他方法高 6.35%。此外，在高校影视艺术教学中应用虚拟仿真技术，能产生显著影响，具有深远的研究意义。本研究的结果可用于改进高校影视艺术教学。
