期刊文献+
共找到3篇文章
< 1 >
每页显示 20 50 100
面向光纤光栅传感线性拟合度的PSO-GPR算法
1
作者 钱敏 桂林 +2 位作者 连枭轩 丁美琪 王炼栋 《光通信研究》 北大核心 2024年第4期62-67,共6页
【目的】为了提高光纤布拉格光栅(FBG)传感系统中反射光谱中心波长与外部环境变量之间的线性拟合度,文章提出了使用粒子群优化的高斯过程回归模型应用于FBG应力传感领域。【方法】针对FBG的反射光谱特性,文章研究了对于FBG传感系统在光... 【目的】为了提高光纤布拉格光栅(FBG)传感系统中反射光谱中心波长与外部环境变量之间的线性拟合度,文章提出了使用粒子群优化的高斯过程回归模型应用于FBG应力传感领域。【方法】针对FBG的反射光谱特性,文章研究了对于FBG传感系统在光谱拟合中线性拟合度的影响,通过粒子群算法去寻找高斯过程回归模型中的最优超参数以提升对反射光谱中心波长的预测性能。文章搭建了FBG应力传感实验平台,将FBG铺设在强度梁上,在等强度梁一端施加不同重量的砝码对FBG产生轴向应变,通过光谱仪采集反射光谱数据并使用文章所提模型进行线性拟合分析处理,将未优化的高斯过程回归模型、最大值法、高斯拟合法和质心法得到的结果作为对照组。【结果】结果表明,在掺铒光纤放大器输出功率为10 dBm、传输光纤距离为50 m、光谱仪采样点个数为501的条件下,反射光谱中心波长与砝码重量之间的线性拟合度均优于对照组,文章所提模型的线性拟合度最高能达到0.9519,相较于对照组均有所提升。在501、251、167和126点的光谱采样点条件下,文章所提模型能将系统的线性拟合度提升到0.9900,相较于最大值法最大提升了0.2587。【结论】分析结果表明,使用粒子群优化的高斯过程回归模型能够有效提高FBG应力传感系统的线性拟合度。 展开更多
关键词 光纤布拉格光栅 高斯过程回归 粒子群算法 线性拟合度
下载PDF
Analysis of radar fault prediction based on combined model 被引量:1
2
作者 邵延君 马春茂 潘宏侠 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2016年第1期44-47,共4页
Based on modeling principle of GM(1,1)model and linear regression model,a combined prediction model is established to predict equipment fault by the fitting of two models.The new prediction model takes full advantag... Based on modeling principle of GM(1,1)model and linear regression model,a combined prediction model is established to predict equipment fault by the fitting of two models.The new prediction model takes full advantage of prediction information provided by the two models and improves the prediction precision.Finally,this model is introduced to predict the system fault time according to the output voltages of a certain type of radar transmitter. 展开更多
关键词 grey linear regression model filtting radar fault prediction
下载PDF
Multi-Objective Optimal Approach for Injection Molding Based on Surrogate Model and Particle Swarm Optimization Algorithm 被引量:4
3
作者 陈巍 周雄辉 +1 位作者 王会凤 王婉 《Journal of Shanghai Jiaotong university(Science)》 EI 2010年第1期88-93,共6页
An integrated optimization strategy based on Kriging model and multi-objective particle swarm optimization(PSO) algorithm was constructed.As a new surrogate model technology,Kriging model has better fitting precision ... An integrated optimization strategy based on Kriging model and multi-objective particle swarm optimization(PSO) algorithm was constructed.As a new surrogate model technology,Kriging model has better fitting precision for nonlinear problem.The Kriging model was adopted to replace computer aided engineering(CAE) simulation as fitness function of multi-objective PSO algorithm,and the computation cost can be reduced greatly.By introducing multi-objective handling mechanism of crowding distance and mutation operator to multiobjective PSO algorithm,the entire Pareto front can be approximated better.It is shown that the multi-objective optimization strategy can get higher solving accuracy and computation efficiency under small sample. 展开更多
关键词 injection molding multi-objective optimization particle swarm optimization(PSO) surrogate model Kriging model
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部