A Quantitative Study on Simultaneous Effects of Governing Parameters in Electrospinning of Nanofibers using Modified Neural Network using Genetic Algorithm

Int. J. Chemoinformatics Chem. Eng. Pub Date : 1900-01-01 DOI:10.4018/IJCCE.2017010102

Shayan Seyedin, S. Maghsoodloo, V. Mottaghitalab

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Abstract

Inthisarticle,modifiedneuralnetworksusinggeneticalgorithmswereemployedtoinvestigatethe simultaneouseffectsoffourofthemostimportantparameters,namely;solutionconcentration(C); spinningdistance(d);appliedvoltage(V);andvolumeflowrate(Q)onmeanfiberdiameter(MFD), as well as standard deviation of fiber diameter (StdFD) in electrospinning of polyvinyl alcohol (PVA)nanofibers.Geneticalgorithmoptimizedneuralnetworks(GANN)wereusedformodeling theelectrospinningprocess.Theresultsindicatebetterexperimentalconditionsandmorepredictive abilityofGANNs.Therefore,theapproachofusinggeneticalgorithmstooptimizeneuralnetworksfor modelingtheelectrospinningprocesshasbeensuccessful.RSMcouldbeemployedwhenstatistical analysis,quantitativestudyoftheeffectsoftheparametersandvisualizationoftheresponsesurfaces areofinterest,whereasinthecaseofmodelingtheprocessandpredictingnewconditions,GANN isamorepowerfultoolandpresentsmoredesirableresults. KEywoRdS Electrospinning, Empirical Modeling, Genetic Algorithm Optimized Neural Networks (GANN), Response Surface Methodology

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基于遗传算法改进神经网络的纳米纤维静电纺丝控制参数同步效应定量研究

Inthisarticle，modifiedneuralnetworksusinggeneticalgorithmswereemployedtoinvestigatethe simultaneouseffectsoffourofthemostimportantparameters，namely;solutionconcentration(C); spinningdistance(d);appliedvoltage(V);andvolumeflowrate(Q)onmeanfiberdiameter(MFD)，以及聚乙烯醇电纺丝中纤维直径(StdFD)的标准偏差(PVA)nanofibers.Geneticalgorithmoptimizedneuralnetworks(GANN)wereusedformodeling theelectrospinningprocess。Theresultsindicatebetterexperimentalconditionsandmorepredictive abilityofGANNs。Therefore，theapproachofusinggeneticalgorithmstooptimizeneuralnetworksfor modelingtheelectrospinningprocesshasbeensuccessful。RSMcouldbeemployedwhenstatistical分析，quantitativestudyoftheeffectsoftheparametersandvisualizationoftheresponsesurfaces areofinterest，whereasinthecaseofmodelingtheprocessandpredictingnewconditions，GANN isamorepowerfultoolandpresentsmoredesirableresults。关键词静电纺丝，经验建模，遗传算法优化神经网络，响应面方法

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Int. J. Chemoinformatics Chem. Eng.

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