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ID:31980174
大小:2.87 MB
页数:57页
时间:2019-01-30
《基于粒子群优化算法设计变截面厚微穿孔板吸声结构》由会员上传分享,免费在线阅读,更多相关内容在教育资源-天天文库。
1、sound-absorptionstructurewasintherangeofmoresaturatedovertheentirefrequency;absorptionpropertiesarealsoimprovedcomparedwiththethree-parameteroptimizationafteroptimizingfourparameterswhicharelargeborediameter,smallborediameter,smallboreperforationrateandthethicknessofthecavity.Additionally,
2、comparativeanalyzingabsorptionpropertiesofthetaperedandlogarithmicborerespectively,wefoundthatsound-absorptionperformanceoflogarithmicboreisbetterthanthatoftaperedbore.However,becauseofstructuralcomplexityonlogarithmicbore,thevariousfactorsshouldbetakenintoaccountinactualdesigning,sothatop
3、timumabsorbercanbechosen.Keywords:Thicktaperedmicro-perforatedpanel,Absorber,Sound-absorptionperformance,ParticleswarmoptimizationalgorithmIII万方数据目录第一章绪论...........................................................................................................11.1概述........................
4、.....................................................................................11.2吸声材料的分类..........................................................................................11.3微穿孔板吸声结构国内外研究现状...........................................................21.4本文研究的目的和意义............
5、..................................................................21.5本文研究的主要内容和方法.......................................................................3第二章粒子群优化算法..........................................................................................42.1粒子群优化算法的基本原理....................
6、...................................................42.2粒子群优化算法的数学描述及流程...........................................................52.2.1算法的数学描述................................................................................52.2.2控制参数设置........................................................
7、............................52.2.3算法流程............................................................................................62.3粒子群优化算法的性能测试.......................................................................72.4粒子群优化算法的应用.............................
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