Physical Education Department of Tianjin University of Science and Technology, Tianjin, China.
Physical Education of Tianjin Business Vocational College, Tianjin, China.
Comput Intell Neurosci. 2022 May 28;2022:2835992. doi: 10.1155/2022/2835992. eCollection 2022.
The spread of Chinese martial arts is crucial for the world to understand Chinese culture. If only relying on one transmission method, it will lead to the difference of transmission and its lack of certain real time. This will lead to differences in the understanding of Chinese martial arts, which is also not conducive to the spread of Chinese glorious culture. Cross-media communication technology can solve this communication difference problem very well. The deep neural network method was used to fuse relevant features of Chinese martial arts, and it also analyzes the feasibility of neural network technology in cross-media communication. At the same time, this study uses deep neural network to study the timeliness of Chinese martial arts in the process of cross-media communication. The research results show that the convolutional neural network can effectively extract the characteristics of Chinese martial arts and carry out effective dissemination. However, the hybrid convolutional neural network with temporal features has higher accuracy in extracting Chinese martial arts features. This hybrid convolutional neural network is more conducive to the dissemination of Chinese martial arts through cross-media technology, which can ensure its timeliness. The maximum error of deep neural network technology in predicting Chinese martial arts culture is only 2.67%. This part of the error comes from the action characteristics of Chinese martial arts culture, which shows that neural network technology has good feasibility.
中国武术的传播对于世界了解中国文化至关重要。如果仅仅依靠一种传播方式，会导致传播的差异和一定程度上的实时性缺失。这将导致人们对中国武术的理解产生差异，也不利于中国光辉文化的传播。跨媒体传播技术可以很好地解决这种传播差异问题。该研究使用深度神经网络方法融合中国武术的相关特征，并分析神经网络技术在跨媒体传播中的可行性。同时，本研究使用深度神经网络研究中国武术在跨媒体传播过程中的实时性。研究结果表明，卷积神经网络可以有效地提取中国武术的特征并进行有效传播。然而，具有时间特征的混合卷积神经网络在提取中国武术特征方面具有更高的准确性。这种混合卷积神经网络更有利于通过跨媒体技术传播中国武术，可以保证其实时性。深度神经网络技术在预测中国武术文化方面的最大误差仅为 2.67%。这部分误差来自中国武术文化的动作特征，表明神经网络技术具有良好的可行性。
