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1、數(shù)據(jù)挖掘分析中蟻群算法的應(yīng)用與研究-->摘要:隨著互聯(lián)網(wǎng)的迅速發(fā)展和普及,廣大entandpopularizationoftheInter,therearemoreandmoreajorityofITmanagersandresearcherstogainstudyinformationresources.Researcherscangetdomesticandinternationaldataresourcessynchronouslyetime,entandaccumulationofstudyinformation,itbeeshardertoretrieveusefuld
2、atafrommassivescientificandtechnologicalinformation.Fortunately,thegenerationofdataminingtechnologyhavesolvedproblemsofinformationanalysisandprocessinginmanyaspects.Thispaperintroducestheantcolonyalgorithmdescribesthetheoreticalbasisanddataminingresearchbackground,purposeandsignificanceofrese
3、archmethodsandframeprovedantcolonyclusteringalgorithmforthepurposeoftheclusteringalgorithmandthecharacteristicsofeachantcolonyoptimizationandimprovementstrategies,re-AntColonyClusteringAlgorithmpointaboutthesimilarityintheaverageprobabilityofconversionfunctionstoimproveandimplementimprovedpro
4、cesses.Testbythenumberofmachinelearning.Accordingtotheimprovedalgorithmbasedonantcolonyclustering(EAC)izationbyantcoloniesProceedingsofthe1stEuropeanConferenceonArtificialLife,1991,134--142.3DorigoM,Optimization,learningandnaturalalgorithms.PhD.Thesis,DepartmentofElectronics,PoliteicodiMilano
5、,Italy,1992.4DorigoM,ManiezzoV,ColomiA.Antsystem:optimizationbyaco-->lonycooperatingagents.IEEETransactiononSystem,Man,andCybemetics—PartB,1996,26(1):29-41.5張紀會.自適應(yīng)蟻群算法[J].控制理論與應(yīng)用,2001,17(1):115~118.6權(quán)光日.集合覆蓋問題的啟發(fā)函數(shù)算法[J].軟件學報,1998,9(2)1378-1396.7王穎,謝劍英.一種白適應(yīng)蟻群算法及其仿真研究計算機數(shù)據(jù)庫[J].系統(tǒng)仿真學報,2002,14(
6、1):31~33.8黃國銳,曹先彬,干煦法.基丁信息素擴散的蟻群算法[J].電子學報,2004,32(5):865-868.9胡小兵,黃席樾.基丁混合行為蟻群算法的研究[J].控制與決策,2005,20(1):69~71.10王玨,周志華,周傲英主編.機器學習及其應(yīng)用[M].北京:清華大學出版社,2006.11李桂林,陳曉云.關(guān)于聚類分析中相似度的討論[J].計算機工程與應(yīng)用,2004,31.12胡建軍,唐常杰,李川,彭京,元昌,陳安龍,蔣永光.基于最近鄰優(yōu)先的高效聚類算法[J].四川大學學報,2004,36(6).13鄭巖.數(shù)據(jù)聚類及其應(yīng)用研究[D].博士學位論文:吉林大學,2
7、003.14張昭濤.數(shù)據(jù)挖掘聚類算法研究[D].碩士學位論文:西南交通大學,2005.15湯效琴,戴汝源.數(shù)據(jù)挖掘中聚類分析的技術(shù)方法明.微計算機信息息,2003,19(1).16李瑞.蟻群聚類算法及其在推薦系統(tǒng)中的應(yīng)用[D].學位論文.重慶:西南師范大學.200517劉波.一種利用信息熵的群體智能聚類算法[J].計算機工程與應(yīng)用,2004,35.180-18218楊新斌,孫京浩,黃道.一種進化聚類學習新方法[J].計算機工程與應(yīng)用,2003:39(15):60-6219熊偉清,