Prediction of thermal conductivity of polymer-based composites by using support vector regression |
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Authors: | WANG GuiLian CAI CongZhong PEI JunFang & ZHU XingJian |
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Affiliation: | WANG GuiLian,CAI CongZhong*,PEI JunFang & ZHU XingJian Department of Applied Physics,Chongqing University,Chongqing 400044,China |
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Abstract: | Support vector regression (SVR) combined with particle swarm optimization (PSO) for its parameter optimization, was proposed to establish a model to predict the thermal conductivity of polymer-based composites under different mass fractions of fillers (mass fraction of polyethylene (PE) and mass fraction of polystyrene (PS)). The prediction performance of SVR was compared with those of other two theoretical models of spherical packing and flake packing. The result demonstrated that the estimated errors by l... |
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Keywords: | polymer matrix composites thermal conductivity support vector regression regression analysis prediction |
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