本文選題：人工化學(xué)反應(yīng) + 支持矢量回歸機(jī)��； 參考：《中國機(jī)械工程》2016年14期

【摘要】：智能減壓閥可通過控制膜片缸壓力實(shí)現(xiàn)出口壓力的智能調(diào)節(jié)。膜片缸壓力是智能減壓閥控制器的控制目標(biāo),因此需要依據(jù)進(jìn)口壓力和出口目標(biāo)壓力對膜片缸壓力進(jìn)行預(yù)測。基于此,提出了基于人工化學(xué)反應(yīng)優(yōu)化算法的支持向量回歸機(jī)(ACROA-SVR)參數(shù)優(yōu)化方法,并將ACROA-SVR應(yīng)用于智能減壓閥膜片缸壓力預(yù)測,采用實(shí)驗(yàn)數(shù)據(jù)將ACROA-SVR與基于遺傳算法的SVR和傳統(tǒng)SVR進(jìn)行了對比,分析結(jié)果表明了ACROA-SVR的有效性和優(yōu)越性。
[Abstract]:The intelligent pressure reducing valve can realize the intelligent adjustment of the outlet pressure by controlling the pressure of the diaphragm cylinder.The pressure of diaphragm cylinder is the control target of intelligent valve controller, so it is necessary to predict the pressure of diaphragm cylinder based on inlet pressure and outlet pressure.Based on this, a parameter optimization method of support vector regression machine (SVM) based on artificial chemical reaction optimization algorithm is proposed, and ACROA-SVR is applied to predict the pressure of diaphragm cylinder of intelligent pressure reducing valve.The experimental data are used to compare ACROA-SVR with SVR based on genetic algorithm and traditional SVR. The results show the effectiveness and superiority of ACROA-SVR.
【作者單位】： 湖南大學(xué);湖南省特大口徑電站閥門工程技術(shù)研究中心;
【基金】：國家科技重點(diǎn)專項(xiàng)(2011ZX07412-001-02)
【分類號(hào)】：TH134
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本文編號(hào)：1736240