Data Sharing Method of College Dance Teaching Resource Database Based on PSO Algorithm

Autor: Xulong ZhuGe, Haibin Cao
Rok vydání: 2022
Předmět:
Zdroj: Computational Intelligence and Neuroscience. 2022:1-9
ISSN: 1687-5273
1687-5265
Popis: 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.
Databáze: OpenAIRE
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