粒子群优化算法的若干改进与应用

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1、Inthispaper，thestudyofparticleswarmoptimizationalgorithmsignificance，andthenwiththeintroductionofPSOstudysomebaslcquestions，includingthebasicconceptsofoptimizationandclassltlcatlonmethods．Subsequently，fromthebasicstructureofPSOalgorlthm，theaIgor．ithmfeaturestoimprovethemethodsofimplementati

2、onmodelsandapplicationsysternstodomoreresearch．Themainresearchcontentofthefollowingareas：．PSOaIgorithrnfortheexistinglocalextremumvulnerable，slowconvergenceandpooraccuracydeficiencies，amethodofaslmPlltled'mainlvforthecharacteristicsofparticleswarmoptimizationandthecharacteristicsoftheformul

3、aitself,thestandardalgorithmPronetoprematureconvergenceandpoorperformancecharacteristicsofthegIobalconvergence，andsomeothermethod，oftenmakingchangesinmorecomplexaIgorithms，inordertoavoidtheseproblems·Theuseofasimplifiedidea，onetypeoffunctionfortheoptimizationproblemcanbesimpliftedcalculatio

4、n，theuseofsimplifiedPSOwithinertlawelghtcorrespondingtobreakthroughtheclassicalalgorithmofinertlawelghtrange，throughthesimulationresultsachievedgoodresults·Chaosasawide．rangingnatureofnonlinearphenomena，random，ergodicity，sensitivitytoinitialconditions，withstabilityandlnstabl11tY，thelong-te珊

5、behavioroftheunpredictabilityofthecharacterlstlcsoioptimizationproblemsforcharacteristicsofchaoticseriesusedtoinitializethepositionandspeedofparticles，nottochangetheparticleswarmoptimizationalgorithmisinitializedwiththetimeoftherandomnatureoftheuseofchaosandenhancethediversityofspeciesandpa

6、rtlclesearchergodicity，atalargeamountoftheinitialgrouponthebasis0fmerlttromtheinitialgroups．Atthesametimeiterationintheevolution，therearequestionsprecociousalgorithmcanintroduceachaoticsequenceofsearchaIgorithmscanbegeneratedintheiterativeoptimalsolutionofanumberotlocalneighborhood，theinert

7、particlestohelpescapefromlocalmlnlmumpointsandfastsearchtotheoptimalsolution·PSOaIgor·ithmbasedontheexistenceofthebackeasllyIntolocaloptimization，prematureconvergenceproblemappears，manystudlesnaVefocusedontheparametersofinertiaweightontheimprovement，beca