Data Sharing Method of College Dance Teaching Resource Database Based on PSO Algorithm
Aiming at the problems of long sharing time, low accuracy, recall, and F1 value in the traditional data sharing method of college dance teaching resource database, a data sharing method of college dance teaching resource database based on PSO algorithm is proposed. Multiple regression KNN method is...
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| Published in | Computational intelligence and neuroscience Vol. 2022; pp. 1 - 9 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Hindawi
17.08.2022
John Wiley & Sons, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1687-5265 1687-5273 1687-5273 |
| DOI | 10.1155/2022/2162981 |
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| Abstract | Aiming at the problems of long sharing time, low accuracy, recall, and F1 value in the traditional data sharing method of college dance teaching resource database, a data sharing method of college dance teaching resource database based on PSO algorithm is proposed. Multiple regression KNN method is used to eliminate the data noise of college dance teaching resource database, so as to obtain the missing value and complete the filling of incomplete data of college dance teaching resource database. Taking the preprocessed data as the basic element of transmission object statistics and analysis, establish the data transmission self-service channel of college dance teaching resource database, calculate the similarity of the data according to the unequal length sequence, and use the partial least square method to complete the feature extraction of the resource database data. According to the feature extraction results, particle swarm optimization algorithm is adopted to share the data of college dance teaching resource database. The simulation results show that the accuracy, recall, and F1 value of the data sharing method of college dance teaching resource database based on PSO algorithm are high, and the sharing time is short. |
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| AbstractList | Aiming at the problems of long sharing time, low accuracy, recall, and F1 value in the traditional data sharing method of college dance teaching resource database, a data sharing method of college dance teaching resource database based on PSO algorithm is proposed. Multiple regression KNN method is used to eliminate the data noise of college dance teaching resource database, so as to obtain the missing value and complete the filling of incomplete data of college dance teaching resource database. Taking the preprocessed data as the basic element of transmission object statistics and analysis, establish the data transmission self-service channel of college dance teaching resource database, calculate the similarity of the data according to the unequal length sequence, and use the partial least square method to complete the feature extraction of the resource database data. According to the feature extraction results, particle swarm optimization algorithm is adopted to share the data of college dance teaching resource database. The simulation results show that the accuracy, recall, and F1 value of the data sharing method of college dance teaching resource database based on PSO algorithm are high, and the sharing time is short.Aiming at the problems of long sharing time, low accuracy, recall, and F1 value in the traditional data sharing method of college dance teaching resource database, a data sharing method of college dance teaching resource database based on PSO algorithm is proposed. Multiple regression KNN method is used to eliminate the data noise of college dance teaching resource database, so as to obtain the missing value and complete the filling of incomplete data of college dance teaching resource database. Taking the preprocessed data as the basic element of transmission object statistics and analysis, establish the data transmission self-service channel of college dance teaching resource database, calculate the similarity of the data according to the unequal length sequence, and use the partial least square method to complete the feature extraction of the resource database data. According to the feature extraction results, particle swarm optimization algorithm is adopted to share the data of college dance teaching resource database. The simulation results show that the accuracy, recall, and F1 value of the data sharing method of college dance teaching resource database based on PSO algorithm are high, and the sharing time is short. Aiming at the problems of long sharing time, low accuracy, recall, and F1 value in the traditional data sharing method of college dance teaching resource database, a data sharing method of college dance teaching resource database based on PSO algorithm is proposed. Multiple regression KNN method is used to eliminate the data noise of college dance teaching resource database, so as to obtain the missing value and complete the filling of incomplete data of college dance teaching resource database. Taking the preprocessed data as the basic element of transmission object statistics and analysis, establish the data transmission self-service channel of college dance teaching resource database, calculate the similarity of the data according to the unequal length sequence, and use the partial least square method to complete the feature extraction of the resource database data. According to the feature extraction results, particle swarm optimization algorithm is adopted to share the data of college dance teaching resource database. The simulation results show that the accuracy, recall, and F1 value of the data sharing method of college dance teaching resource database based on PSO algorithm are high, and the sharing time is short. |
| Audience | Academic |
| Author | Cao, Haibin ZhuGe, Xulong |
| AuthorAffiliation | 2 Jiangsu Normal University Academy of Music, Jiangsu, Xuzhou 221116, China 1 School of Preschool Education, Linyi Vocational College, Linyi 276000, China |
| AuthorAffiliation_xml | – name: 2 Jiangsu Normal University Academy of Music, Jiangsu, Xuzhou 221116, China – name: 1 School of Preschool Education, Linyi Vocational College, Linyi 276000, China |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36035821$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.4236/jss.2020.83044 10.1088/1742-6596/1744/3/032004 10.1088/1742-6596/1852/2/022049 10.18686/ahe.v3i2.1444 10.1016/j.procs.2021.03.002 10.1088/1742-6596/1916/1/012191 10.1049/cje.2020.07.003 10.1088/1742-6596/1345/5/052072 10.1021/acs.jcim.0c01389 10.1080/10496505.2021.1891923 |
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| Copyright | Copyright © 2022 Xulong ZhuGe and Haibin Cao. COPYRIGHT 2022 John Wiley & Sons, Inc. Copyright © 2022 Xulong ZhuGe and Haibin Cao. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 Copyright © 2022 Xulong ZhuGe and Haibin Cao. 2022 |
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| SubjectTerms | Adjustment Algorithms Colleges & universities Computer Simulation Dance Dancing Data retrieval Data transmission Equipment and supplies Feature extraction Higher education Humans Information Dissemination Information sharing Information sources Information technology Least-Squares Analysis Mathematical optimization Methods Multimedia Optimization Particle swarm optimization Recall Statistical analysis Teaching |
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| Title | Data Sharing Method of College Dance Teaching Resource Database Based on PSO Algorithm |
| URI | https://dx.doi.org/10.1155/2022/2162981 https://www.ncbi.nlm.nih.gov/pubmed/36035821 https://www.proquest.com/docview/2707458234 https://www.proquest.com/docview/2707879434 https://pubmed.ncbi.nlm.nih.gov/PMC9402334 https://downloads.hindawi.com/journals/cin/2022/2162981.pdf |
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