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Optimization of Laser Ablation Technology for PDPhSM Matrix Nanocomposite Thin Film by Artificial Neural Networks-particle Swarm Algorithm 被引量:3
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作者 唐普洪 宋仁国 《Journal of Wuhan University of Technology(Materials Science)》 SCIE EI CAS 2010年第2期188-193,共6页
A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane (TPDC) based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method ... A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane (TPDC) based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method facilitates the synthesis of polydiphenysilylenemethyle (PDPhSM) thin film, which is difficult to make by conventional methods because of its insolubility and high melting point. TPDC was first evaporated on silicon substrates and then exposed to metal nanoparticles deposition by pulsed laser ablation prior to heat treatment.The TPDC films with metal nanoparticles were heated in an electric furnace in air atmosphere to induce ring-opening polymerization of TPDC. The film thicknesses before and after polymerization were measured by a stylus profilometer. Since the polymerization process competes with re-evaporation of TPDC during the heating, the thickness ratio of the polymer to the monomer was defined as the polymerization efficiency, which depends greatly on the technology conditions. Therefore, a well trained radial base function neural network model was constructed to approach the complex nonlinear relationship. Moreover, a particle swarm algorithm was firstly introduced to search for an optimum technology directly from RBF neural network model. This ensures that the fabrication of thin film with appropriate properties using pulsed laser ablation requires no in-depth understanding of the entire behavior of the technology conditions. 展开更多
关键词 nanocomposite thin film pulsed laser deposition(PLD) artificial neural net- worksann particle swarm optimization (PSO)
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快走丝电火花线切割加工工艺参数的优化选取 被引量:7
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作者 楼乐明 李明辉 彭颖红 《上海交通大学学报》 EI CAS CSCD 北大核心 2000年第10期1441-1443,共3页
基于快走丝电火花线切割加工机床性能的发挥在很大程度上依赖于操作人员的技术水平 ,用神经网络技术建立快走丝线切割加工工艺模型 .与实验数据的比较表明 ,模型能精确地预测出给定条件下的切割速度和表面粗糙度 ,反映了该机床的加工工... 基于快走丝电火花线切割加工机床性能的发挥在很大程度上依赖于操作人员的技术水平 ,用神经网络技术建立快走丝线切割加工工艺模型 .与实验数据的比较表明 ,模型能精确地预测出给定条件下的切割速度和表面粗糙度 ,反映了该机床的加工工艺规律 .在此基础上根据工件的实际厚度和表面粗糙度要求得到最优的加工参数组合 ,克服了工艺参数表的局限性 . 展开更多
关键词 电火花线切割加工 工艺建模 优化选取
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应用神经网络定量表示热敏液晶的色/温特性
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作者 朱双东 《石油化工高等学校学报》 CAS 1996年第4期42-44,54,共4页
热敏液晶是近年来图象测量技术研究工作中采用的一种新型传感元件,介绍了它的色/温转换特性,并采用神经网络来解决用传统方法难以实现的色/温转换特性的定量表示问题,取得了良好的效果。
关键词 热敏液晶 流体温度场 图象测量 神经网络
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