| 基于人工神经网络-粒子群算法激光烧蚀制备PDPhSM基纳米复合薄膜的工艺优化 |
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| 引用本文： | 唐普洪,宋仁国,柴国钟,毛杰.基于人工神经网络-粒子群算法激光烧蚀制备PDPhSM基纳米复合薄膜的工艺优化[J].材料科学与工艺,2009,17(1):122-125,128. |
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| 作者姓名： | 唐普洪 宋仁国 柴国钟 毛杰 |
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| 作者单位： | 唐普洪,TANG Pu-hong(浙江工业大学机械制造及自动化教育部重点实验室,浙江,杭州,310014;嘉兴职业技术学院机电与汽车分院,浙江,嘉兴,314036);宋仁国,柴国钟,SONG Ren-guo,CHAI Guo-zhong(浙江工业大学机械制造及自动化教育部重点实验室,浙江,杭州,310014);毛杰,MAO Jie(嘉兴职业技术学院机电与汽车分院,浙江,嘉兴,314036)
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| 基金项目： | 浙江省自然科学基金青年科技人才培养基金，浙江省教育厅专项项目 |
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| 摘 要： | 为有效缩短脉冲激光烧蚀制备有机硅聚合物聚二苯基硅亚甲基硅烷(Polydiphenylsilylenemethyle,PDPhSM)基纳米复合薄膜工艺中繁琐的试验过程,本文将用径向基函数(Radial BasisFunction,RBF)人工神经网络对聚合物PDPhSM基纳米复合薄膜的制备工艺与聚合效率之间的关系进行建模;讨论了激光能量密度、环境压强、靶衬距离、沉积时间和聚合效率之间的关系.在此基础上,采用粒子群(Particle Swarm Optimiza-tion,PSO)算法对其进行工艺优化,200代以后,粒子素质明显提高,k值趋近于0,群体达到了最优,工艺参数的优化结果较为满意.从而为薄膜材料工艺优化研究探索了一条崭新的途径.
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| 关 键 词： | PDPhSM基纳米复合薄膜 激光烧蚀 径向基函数神经网络 聚合效率 粒子群优化 |
Optimization of laser ablation technology for PDPhSM matrix nanocomposite thin film based upon artificial neural networks-particle swarm algorithm |
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| TANG Pu-hong,SONG Ren-guo,CHAI Guo-zhong,MAO Jie.Optimization of laser ablation technology for PDPhSM matrix nanocomposite thin film based upon artificial neural networks-particle swarm algorithm[J].Materials Science and Technology,2009,17(1):122-125,128. |
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| Authors: | TANG Pu-hong SONG Ren-guo CHAI Guo-zhong MAO Jie |
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| Affiliation: | 1.The MOE Key Laboratory of Mechanical Manufacture and Automation,Zhejiang University of Technology,Hangzhou 310014,China;2.Department of Mechanical and Automobile Engineering,College of Jiaxing Vocational Technology,Jiaxing 314036,China |
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| Abstract: | To optimize the process of fabricating polydiphenysilylenemethylene (PDPhSM) thin films,a new method involved artificial neural networks particle swarm algorithm is introduced.we use RBF neural networks to construct a model of laser-ablation conditions and polymerization efficiency,and then use this model to establish the nonlinear relationship between technology parameters(laser fluence,ambient pressure,distance between target and substrate,deposition time) and polymerization efficiency. Moreover,we use th... |
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| Keywords: | PDPhSM matrix nanocomposite thin film laser ablation radial basis function neural networks polymerization efficiency particle swarm optimization |
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