基于人工螢火蟲(chóng)算法優(yōu)化GM(1 ,1)模型在變形監(jiān)測(cè)數(shù)據(jù)處理中的應(yīng)用研究_2814.pdf

1、摘要I畢業(yè)論文題目：基于人工螢火蟲(chóng)算法優(yōu)化GM(11)模型在變形監(jiān)測(cè)數(shù)據(jù)處理中的應(yīng)用研究大地測(cè)量學(xué)與測(cè)量工程專(zhuān)業(yè)2010級(jí)碩士生姓名郭旭平指導(dǎo)教師（姓名、職稱(chēng)）：吳良才教授摘要目前，如何實(shí)時(shí)、科學(xué)、準(zhǔn)確地分析和預(yù)報(bào)建筑物、構(gòu)筑物的變形，已成為科學(xué)研究以及指導(dǎo)實(shí)踐的一個(gè)重大課題。本文通過(guò)變形監(jiān)測(cè)數(shù)據(jù)處理及分析的預(yù)測(cè)模型——GM(11)模型的國(guó)內(nèi)外研究現(xiàn)狀，以及一種新型的智能優(yōu)化算法——人工螢火蟲(chóng)算法的國(guó)內(nèi)外的方研究現(xiàn)狀，搜集大量資料，對(duì)比

2、分析，構(gòu)思自己研究的方法，采用人工螢火蟲(chóng)算法將灰色GM(11)模型進(jìn)行優(yōu)化，應(yīng)用于變形監(jiān)測(cè)預(yù)報(bào)與分析工作中，其主要研究?jī)?nèi)容包括：本文利用最小一乘法建立目標(biāo)函數(shù)，再通過(guò)人工螢火蟲(chóng)算法優(yōu)化，求解目標(biāo)函數(shù)，從而使GM(11)模型得到優(yōu)化，隨后給出了優(yōu)化模型的實(shí)施步驟以及基本流程。在對(duì)預(yù)測(cè)效果檢驗(yàn)時(shí)，用該優(yōu)化模型計(jì)算參考文獻(xiàn)里數(shù)據(jù)，并與文獻(xiàn)中的其它模型相比較，證明優(yōu)化模型的可行性及優(yōu)越性。把人工螢火蟲(chóng)算法優(yōu)化的GM(11)模型應(yīng)用到變形監(jiān)測(cè)中，

3、對(duì)沉降數(shù)據(jù)進(jìn)行處理、分析。并從殘差、相對(duì)誤差、發(fā)展系數(shù)、后驗(yàn)方差值c四個(gè)方面比較和驗(yàn)證優(yōu)化模型，利用實(shí)驗(yàn)結(jié)果證明研究方法的可行性，優(yōu)化模型的優(yōu)越性。實(shí)例結(jié)果顯示，人工螢火蟲(chóng)算法優(yōu)化的GM(11)模型在殘差、相對(duì)誤差、發(fā)展系數(shù)、后驗(yàn)方差值c等方面的確優(yōu)越GM(11)模型，本文采用的模型進(jìn)一步擴(kuò)大了灰色GM(11)模型應(yīng)用的范圍。關(guān)鍵詞：關(guān)鍵詞：變形監(jiān)測(cè)；灰色系統(tǒng)理論；人工螢火蟲(chóng)算法；GM(11)模型；最小一乘法AbstractIIITHE

4、SIS:BasedonglowwmswarmoptimizationGM(11)modelSettlementdataapplicationstudyinSettlementMonitingSPECIALIZATION:GeodesySurveyEngineeringPOSTGRADUATE:XupingGuoMENT:ProfessLiangcaiWUAbstractNowadayshowcanrealtimelyscientific

5、allyaccuratelyanalysisfecastinginthedefmationofbuildingsstructures.Ithasbecomeamajtopicinthepracticeofscientificresearchguidance.InthispaperdefmationmonitingdataprocessinganalysispredictionmodelGM(11)modelresearchstatusa

6、thomeabroadaswellasanewtypeofintelligentoptimizationalgithmglowwmswarmoptimizationsquareResearchcollectlargeamountsofdatacomparativeanalysis.theglowwmswarmoptimizationofgrayGM(11)modelisappliedtodefmationmonitingfecastin

7、ganalysisitmainlyincludesasthefollows:ThisarticlebuildsobjectivefunctionwiththeLogarithmsolvestheobjectivefunctionwiththeglowwmswarmoptimization.SothattheGM(11)modelhasbeenoptimized.Atthesametimeitgiventheimplementations

8、tepsaswellasthebasicprocessesoftheoptimizationmodel.Testedthepredictedeffecttheoptimizationmodelfcalculatingthereferenceliteraturedatacomparedwithothermodelsintheliteraturetoprovethefeasibilitysuperiityoftheoptimizationm

9、odel.AftertheGM(11)modeloftheglowwmswarmoptimizationisappliedtothedefmationmonitingonsettlementdataprocessinganalysising.Fromtheresidualstherelativeerrthedevelopmentcoefficienttheposterivariancecvalueofthefouraspectsofco

10、mparisonverificationoptimizationmodelwhichshowedthesuperiityoftheoptimizationmodel.Theexperimentalresultsshowthefeasibilityoftheresearchmethodsindicatingthesuperiityoftheoptimizationmodel.Theresultsofexamplesshowglowwmsw

11、armoptimizationoptimizedGM(11)modelisindeedsuperiintermsofresidualsrelativeerrthecoefficientofdevelopmentafterthepreiondifferencecintheGM(11)modelThemodelusedinthispaperexptherangeofgrayGM(11)modelapplication.Keywds:defm