Welcome to Scholar Publishing Group

International Journal of Educational Innovation and Science, 2023, 4(1); doi: 10.38007/IJEIS.2023.040108.

Music Teaching Innovation in Primary and Secondary Schools based on Genetic Algorithm and Artificial Neural Network

Author(s)

Jianbing Xi

Corresponding Author:
Jianbing Xi
Affiliation(s)

Philippine Christian University, Manila, Philippines

Abstract

At present, the academia has explored the innovation research of music teaching (MT) in PASS. Researchers have applied the combination of genetic algorithm (GA) and neural network (NN) to English teaching innovation, which has greatly improved the efficiency of English teaching. For this reason, this paper briefly analyzes GA and NN technology, and combines them to analyze the feasibility. Through the combination of GA and artificial NN, it is applied to the innovation research of MT in primary and secondary schools (PASS). With spectrum reading teaching as the main research object, it is proposed to carry out spectrum reading teaching with various technical means in combination with the algorithm. Finally, it is investigated and analyzed through experiments; it verifies the effectiveness of the innovative methods of MT in PASS proposed in this paper.

Keywords

Genetic Algorithm, Artificial Neural Network, Music Teaching in Primary and Secondary Schools, Teaching Innovation Research

Cite This Paper

Jianbing Xi. Music Teaching Innovation in Primary and Secondary Schools based on Genetic Algorithm and Artificial Neural Network. International Journal of Educational Innovation and Science (2023), Vol. 4, Issue 1: 99-108. https://doi.org/10.38007/IJEIS.2023.040108.

References

[1] Li Su, Qing Jiang. Erratum: A Knowledge-Based System for Children's Music Teaching Strategies Based on the Inheritance of Local Music Culture in Southern Jiangsu. Int. J. Pattern Recognit. Artif. Intell. (2022) 36(9): 2292001:1-2292001:2.

[2] Changfei Tang, Jun Zhang. An intelligent deep learning-enabled recommendation algorithm for teaching music students. Soft Comput. (2022) 26(20): 10591-10598.

[3] Juhan Nam, Keunwoo Choi, Jongpil Lee, Szu-Yu Chou, Yi-Hsuan Yang. Deep Learning for Audio-Based Music Classification and Tagging: Teaching Computers to Distinguish Rock from Bach. IEEE Signal Process. Mag. (2019) 36(1): 41-51.

[4] A. Jameer Basha, S. Aswini, S. Aarthini, Yunyoung Nam, Mohamed Abouhawwash. Genetic-Chicken Swarm Algorithm for Minimizing Energy in Wireless Sensor Network. Comput. Syst. Sci. Eng. (2023) 44(2): 1451-1466.

[5] K. Jagadeesh, A. Rajendran. Improved Model for Genetic Algorithm-Based Accurate Lung Cancer Segmentation and Classification. Comput. Syst. Sci. Eng. (2023) 45(2): 2017-2032.

[6] M. Mythreyee, A. Nalini. Genetic Algorithm Based Smart Grid System for Distributed Renewable Energy Sources. Comput. Syst. Sci. Eng. (2023) 45(1): 819-837.

[7] Seyed Mahdi Homayouni, Dalila B. M. M. Fontes, José Fernando Gonçalves. A multistart biased random key genetic algorithm for the flexible job shop scheduling problem with transportation. Int. Trans. Oper. Res. (2023) 30(2): 688-716. 

[8] Elena L. Kulida. Genetic Algorithm for Solving the Problem of Optimizing Aircraft Landing Sequence and Times. Autom. Remote. Control. (2022) 83(3): 426-436.

[9] K. Kamaraj, B. Lanitha, S. Karthic, P. N. Senthil Prakash, R. Mahaveerakannan. A Hybridized Artificial Neural Network for Automated Software Test Oracle. Comput. Syst. Sci. Eng. (2023) 45(2): 1837-1850.

[10] Polin Rahman, Ahmed Rifat, Md. Iftehadamjad Chy, Mohammad Monirujjaman Khan, Mehedi Masud, Sultan Aljahdali. Machine Learning and Artificial Neural Network for Predicting Heart Failure Risk. Comput. Syst. Sci. Eng. (2023) 44(1): 757-775

[11] Junaid Rashid, Sumera Kanwal, Muhammad Wasif Nisar, Jungeun Kim, Amir Hussain. An Artificial Neural Network-Based Model for Effective Software Development Effort Estimation. Comput. Syst. Sci. Eng. (2023) 44(2): 1309-1324.

[12] Roman Englert, Jörg Muschiol. Numerical Evidence That the Power of Artificial Neural Networks Limits Strong AI. Adv. Artif. Intell. Mach. Learn. (2022) 2(2): 338-346.

[13] Zhou K, Li S, Cao R, et al. Optimal technology innovation of teaching buildings for primary and middle schools based on compound negative pressure ventilation. Applied Nanoscience, 2022, 13(3):2037-2048.

[14] Xu J S. A Spatial Supply-Demand Imbalance Between Rural Primary and Secondary Schools in Shaanxi Province Based on Road Network Analysis, 2022, 6(2):17-26.

[15] Bülbül, Mehmet Akif, ztürk, Celal. Optimization, Modeling and Implementation of Plant Water Consumption Control Using Genetic Algorithm and Artificial Neural Network in a Hybrid Structure. Arabian Journal for Science and Engineering, 2022, 47(2):2329-2343.

[16] Chen X, He L, Li Q, et al. Non-invasive prediction of microsatellite instability in colorectal cancer by a genetic algorithm–enhanced artificial neural network–based CT radiomics signature. European Radiology, 2023, 33(1):11-22.