基于距离排序的DUPSO-DSVM民歌快速分类算法研究  

A folk songs fast classification algorithm DUPSO-DSVM based on distance sorting

作　　者：吕小姣 张玉梅 杨红红[2,3] 吴晓军 LÜXiao-jiao;ZHANG Yu-mei;YANG Hong-hong;WU Xiao-jun(Key Laboratory of Intelligent Computing and Service Technology for Folk Song,Ministry of Culture and Tourism,Xi’an 710119;School of Computer Science,Shaanxi Normal University,Xi’an 710119;Key Laboratory of Modern Teaching Technology,Ministry of Education,Shaanxi Normal University,Xi’an 710062,China)

机构地区：[1]民歌智能计算与服务技术文化和旅游部重点实验室,陕西西安710119 [2]陕西师范大学计算机科学学院,陕西西安710119 [3]陕西师范大学现代教学技术教育部重点实验室,陕西西安710062

出　　处：《计算机工程与科学》2023年第10期1874-1883,共10页Computer Engineering & Science

基　　金：国家自然科学基金(11872036);中央高校基本科研业务费创新团队项目(GK202101004);陕西省创新能力支撑计划(2022TD-26)。

摘　　要：在网络信息快速发展的时代背景下,不同的音乐爱好者对音乐信息检索的需求也在不断提高,音乐分类成为了一个非常值得研究的问题。提出了将耗散均匀搜索粒子群优化算法DUPSO与基于距离排序的支持向量预选取算法DSVM相结合的DUPSO-DSVM民歌快速分类算法。该算法利用DUPSO算法对SVM的惩罚系数C和核函数参数g进行优化,并利用DSVM算法优化DUPSO算法的参数优化时间。实验结果表明,在使用了DUPSO-DSVM算法之后,算法的训练时间只占未使用DUPSO-DSVM算法的26.26%,民歌分类正确率为84%,但仍然保持着较高的分类正确率。In the context of the rapid development of network information,the demand of different music lovers for music information retrieval is also increasing,and music classification has become an important research subject.This paper proposes a fast classification method of DUPSO-DSVM folk songs,which combines dissipative uniform particle swarm optimization(DUPSO)with distance sorted SVM(DSVM).This method uses DUPSO algorithm to optimize the penalty coefficient C and kernel function parameter g of SVM,and uses DSVM algorithm to optimize the parameter optimization time of DUPSO algorithm.The experimental results show that,DUPSO-SVM algorithm has a classification accuracy of 84%.After using DUPSO-DSVM algorithm,the training time of the algorithm only accounts for 26.26%of the unused DUPSO-DSVM algorithm,but it still maintains a high classification accuracy.

关 键 词：民歌分类 特征提取 DUPSO算法 支持向量机 支持向量预选取 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]