基于分散圖決策的ε占優(yōu)多目標(biāo)粒子群算法施羅德聲擴(kuò)散體設(shè)計(jì)
發(fā)布時(shí)間:2018-04-23 15:16
本文選題:聲音擴(kuò)散體 + 多目標(biāo)粒子群。 參考:《科學(xué)技術(shù)與工程》2017年32期
【摘要】:為提高聲音擴(kuò)散體設(shè)計(jì)的合理性降低算法計(jì)算復(fù)雜度,提出基于分散圖決策的ε占優(yōu)多目標(biāo)粒子群算法(ε-MOPSO)的聲音擴(kuò)散體設(shè)計(jì)方法。首先,利用夫瑯禾費(fèi)理論建立施羅德擴(kuò)散的聲音擴(kuò)散特性量化方法,獲得1/3倍頻帶的擴(kuò)散系數(shù);并利用歸一化方式消除極限尺寸下產(chǎn)生的邊緣衍射散射效應(yīng)。其次,構(gòu)建聲音擴(kuò)散體多目標(biāo)優(yōu)化模型,通過對(duì)擴(kuò)散系數(shù)進(jìn)行重設(shè)置,消除擴(kuò)散體重復(fù)和等價(jià)問題。然后采用ε-MOPSO算法,將目標(biāo)空間分割成固定數(shù)量的n個(gè)網(wǎng)格,以保持種群解的多樣性,實(shí)現(xiàn)聲音擴(kuò)散體參數(shù)優(yōu)化;并采用分散圖決策方式實(shí)現(xiàn)最終散體設(shè)計(jì)方案選擇。最后,通過仿真對(duì)3種不同的設(shè)計(jì)模型進(jìn)行了評(píng)價(jià)和選擇。
[Abstract]:In order to improve the rationality of sound diffuser design and reduce the computational complexity of the algorithm, a method of sound diffusion volume design based on 蔚 -MOPSO-based 蔚 -dominated multi-objective particle swarm optimization (蔚 -MOPSO) is proposed. Firstly, by using Fraunhofer's theory, the sound diffusion characteristics of Schroeder diffusion are quantified, and the diffusion coefficient of 1 / 3 times frequency band is obtained, and the edge diffraction scattering effect under the limit size is eliminated by the normalized method. Secondly, the multi-objective optimization model of acoustic diffuser is constructed, and the problem of repetition and equivalence of diffuser is eliminated by re-setting the diffusion coefficient. Then 蔚 -MOPSO algorithm is used to divide the target space into a fixed number of n meshes in order to maintain the diversity of population solutions and optimize the parameters of acoustic diffuser. Finally, three different design models are evaluated and selected by simulation.
【作者單位】: 中國科學(xué)院武漢物理與數(shù)學(xué)研究所;
【基金】:國家自然科學(xué)基金(11404375) 國家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃(2012CB922101)資助
【分類號(hào)】:TP18
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本文編號(hào):1792508
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