Prediction of thermal conductivity of polymer-based composites by using support vector regression

• 作 者: WANG GuiLian CAI CongZhong PEI
• 机 构: DepartmentofAppliedPhysics
• 出 处: 中国科学：物理学、力学、天文学英文版
• 发表日期: 2011年5期
• 关键词: 聚合物基复合材料 支持向量回归 预测性能 热导率 平均绝对误差 粒子群优化算法 质量分数 聚苯乙烯 polymer matrix composites the
• 基金项目: This work was supported by the Program for New Century Excellent Tal- ents in University of China （Grant No. NCET-07-0903）, the Scientific Research Foundation for the Returned Overseas Chinese Scholar

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 (ma