Interactive Music Distance Education Platform Based on RBF Algorithm
Keywords:interactive music, distance education, RBF Algorithm
INTRODUCTION: Since the 21st century, Internet technology has been developing rapidly, and the field of education has gradually broken through the traditional offline teaching mode; utilizing the Internet mode for distance education to break the time and space constraints of education and music education is more restrictive on time and space. However, if distance education can be better utilized to promote the development of online music education, it will promote the development of music education.
OBJECTIVES: This paper combines the past research results of the RBF algorithm, music education and distance education to study the construction of an interactive music distance education platform based on the RBF algorithm. The algorithm is used to improve the quality of the construction of the distance education platform, and the algorithm mainly optimizes the information dissemination path of distance education in the construction of the interactive music distance education platform and improves the reliability of the platform construction.
METHODS: The RBF algorithm is used to optimize the construction of the platform, and the case method is used to study individual schools to detect the actual application of music distance education and to find the strengths and weaknesses of the interactive music distance education platform, and to improve the weaknesses to enhance the platform.
RESULTS: The study found that constructing an interactive music distance education platform will not guarantee the quality of distance education; teachers and students can not quickly realize the effective communication between teachers and students, and some teachers can not better apply the distance education platform. However, there is still room for developing interactive music distance education platforms.
CONCLUSION: The research of interactive music distance education platforms based on the RBF algorithm has a significant positive effect on the development of distance education, art distance education, music education and so on in China. Therefore, it is necessary to continuously improve music education by utilizing online teaching methods and teaching resources.
Aguilar, F. R. The face-to-face and the online learner: A comparative study of tutorial support for Open and Distance Language Learning and the learner experience with audio-graphs SCMC. (2022).14(14), 20.
Bao, Y., Zhu, Y., & Qian, F. A Deep Reinforcement Learning Approach to Improve the Learning Performance in Process Control. Industrial & Engineering Chemistry Research, (2021). 60(15), 34. https://doi.org/10.1021/acs.iecr.0c05678
Bonaventura, L., Fernández-García, S., & Gómez-Mármol, M. Efficient implicit solvers for models of neuronal networks. (2022). 24(24), 2. https://doi.org/10.2139/ssrn.4260036
Brown, M., Skerritt, C., Shevlin, P., Mcnamara, G., & O’Hara, J. Deconstructing the Challenges and Opportunities for Blended Learning in the Post Emergency Learning Era. Irish Educational Studies, (2022). 41(2), 12–17. https://doi.org/10.1080/03323315.2021.2022526
Cao, J., Xiaoping Zhao. An Automated Approach for Execution Sequence-Driven Software and Physical Co-Design of Mechatronic Systems Based on Hybrid Functional Ontology. Computer-Aided Design, (2021). 131(1), 242–250.
Chow, W. Y., Hui, N. N., Li, Z., & Dong, Y. Dialogic teaching in English-as-a-second-language classroom: Its effects on first graders with different levels of vocabulary knowledge. Language Teaching Research, (2021). 136216882098139. https://doi.org/10.1177/1362168820981399
English, H. J., Lumb, M., & Davidson, J. W. What are the affordances of the digital music space in alternative education? A reflection on an exploratory music outreach project in rural Australia: International Journal of Music Education, (2021). 39(3), 275–288. https://doi.org/10.1177/0255761421999731
Filipa, M. B. L., Sundberg, J., & Granqvist, S.. Augmented visual-feedback of airflow: Immediate effects on voice-source characteristics of singing students: Psychology of Music, (2022) 50(3), 933–944. https://doi.org/10.1177/03057356211026735
Fu, Y., & Liu, Y. Contrastive transformer-based domain adaptation for multi-source cross-domain sentiment classification. Knowledge-Based Systems, (2022). 11(Jun.7), 245. https://doi.org/10.1016/j.knosys.2022.108649
Heineke, A. J., & Vera, E. M. Beyond Language and Academics: Investigating Teachers’ Preparation to Promote the Social-Emotional Well-Being of Emergent Bilingual Learners: Journal of Teacher Education, (2022). 73(2), 145–158. https://doi.org/10.1177/00224871211027573
Huang, C. H., & Lin, C. C. K. A novel density-based neural mass model for simulating neuronal network dynamics with conductance-based synapses and membrane current adaptation. Neural Networks, (2021). 4(4), 14–18.
Huang, H., Xue, C., Zhang, W., & Guo, M. Torsion design of CFRP-CFST columns using a data-driven optimization approach—engineering Structures, (2022). 12(251-Jan.15 Pt.A), 23.
Kocanaogullari, A., Akakaya, M., & Erdogmus, D. Stopping Criterion Design for Recursive Bayesian Classification: Analysis and Decision Geometry. IEEE Transactions on Software Engineering, (2021). 11(10), 45.
Lu, Y., Luo, Q., Liao, Y., & Xu, W. Vortex-induced vibration fatigue damage prediction method for flexible cylinders based on RBF neural network. Ocean Engineering, Jun. (2022).15, 254.
Mangaroska, K., Roberto Martinez㎝Maldonado, Vesin, B., & Gaevi, D. Challenges and opportunities of multimodal data in human learning: The computer science students’ perspective. Journal of Computer Assisted Learning, (2021). 12(3), 11. https://doi.org/10.1111/jcal.12542
Schaefer, S. M. The corporate social media creep. Culture and Organization, (2023). 29(2), 124–138. https://doi.org/10.1080/14759551.2022.2153129
Wiener, S., & Bradley, E. D. Harnessing the musician advantage: Short-term musical training affects non-native cue weighting of linguistic pitch: Language Teaching Research, (2023). 27(4), 1016–1031. https://doi.org/10.1177/1362168820971791
Xuan, A., Rothstein, S., Porterfield, Z., Hu, Y., Barranca, V. J., Xuan, A., Rothstein, S., Porterfield, Z., Hu, Y., & Barranca, V. J. Data-Driven Reconstruction and Encoding of Sparse Stimuli across Convergent Sensory Layers from Downstream Neuronal Network Dynamics. SIAM Journal on Applied Dynamical Systems, (2021). 20(20–4), 56.
Zelenkauskaite, A., & Albright, G. Facebook Live is not “liked:” Construction of Liveness and the Reception of Video Livestreaming, accepted in March 2021 by New Media and Society. New Media & Society, (2021). in press(12), 11–17.
Zhang, Y., Hu, X., Hui, Z., Liu, Y., Zhang, Z., & Wang, J. Parameter interval optimization of the DBD plasma actuator based on orthogonal experiment and RBF neural network approximation model. Physics of Plasmas, (2021). 28(2), 023504-. https://doi.org/10.1063/5.0037035
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