欢迎来到天天文库
浏览记录
ID:32085476
大小:4.96 MB
页数:51页
时间:2019-01-31
《支持向量回归机参数优化的方法研究》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、万方数据AbstractTheperformanceofsupportvectorregression(SVR)hasavitalrelationshipwithparameterselection,butevennow,thereisnotadefinitivemathematicaltheorytoguidehowtochoosetheoptimalparameters.Forthepurposeofsolvingthisproblem,theparameterselectionofSVRistransformedtoacombinatorialoptimizationproblem.Th
2、entheoptimizationproblemsissolvedbybothofintelligentalgorithms.Aimingatthedeficiencyofartificialbeecolonyalgorithm(ABC),theweightingfunction,thepresent.optimalfoodsourceandthechaoticsearchalgorithmareintroducedtoimprovetheupdateformsofABCandthesearchmethodofscoutbees.ThentheSVRmodelisproposedbasedon
3、improvedABC.Numericalexperimentationsindicatethattheimprovedalgorithmisfeasibilityandsuperiority.Takingtheshort—termtrafficflowdataasanexample,thepredictiveresultsoftheimprovedABC.SVRiScomparedwithACO—SVR、PSO—SVRandABC—SVR,theresultsindicatethattheimprovedABC—SVRissuperiortothepredictiveeffectoftheo
4、therthree,itsruntimeistheshortestandshowsgoodgeneralizationabilityandlearningability.Aimingatthedisadvantageofartificialfishswarmalgorithm(AFSA)withthelateslowconvergencespeedandlowprecision,theABCisintroducedtoimprovethesearchefficiencyofAFSAandtheAFSA—ABChybridalgorithmisobtained.ThenitisusedforSV
5、Rparameterokmization.NumericalexperimentationsshowthatthealgorithmCansolvetheproblemofparameteroptimization.ThemodelisappliedtopredicttheGDPofShanghaiCity,theresultsindicatethatthemodelissuperiorthantheexistingpredictionmodel,itprovidesanewwayforthepredictionofGDEKeyWords:supportvectorregression;par
6、ameteroptimization;kernelparameter;artificialbeecolonyalgorithm;artificialfishswarlTlalgorithm万方数据目录摘要⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯IAbstract⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯II1绪论⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯.11.1研究背景⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯11.2研究现状及意义⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯21.3研究内容及结构安排⋯⋯⋯⋯⋯⋯⋯⋯⋯
7、⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯32相关基础理论⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯.52.1支持向量回归机⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯..52.1.1损失函数⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯..52.1.2核函数⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯.62.1.3支持向量机的回归⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯82.2人工蜂群算法⋯⋯⋯⋯⋯⋯
此文档下载收益归作者所有