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机构地区:[1]苏州工业职业技术学院,江苏苏州215000 [2]苏州大学计算机科学与技术学院,江苏苏州215000
出 处:《激光杂志》2017年第1期158-162,共5页Laser Journal
基 金:国家自然科学基金(71311358);江苏省自然科学基金(JS2015215);浙江省高等学校访问工程师校企合作项目(G2014056)
摘 要:通过对光纤激光网络中的浪涌突变数据进行优化调度设计,实现对光纤激光网络的准确监测。传统方法采用线性时间序列预测方法进行浪涌突变数据调度,没能有效挖掘光纤激光网络中浪涌突变数据的非线性特征,导致调度的准确性不好。提出基于非线性自相关特征匹配和定量递归图谱分析的光纤激光网络中浪涌突变数据调度方法,对涌浪突变数据进行非线性时间序列分析,根据提取的自相关特征量进行定量递归分析,在递归图谱中提取涌浪突变数据的规则性特征,实现涌浪突变数据优化调度。仿真实验结果表明,采用改进方法进行光纤激光网络的涌浪突变数据调度,其调度准确度及调度性能均要优于传统方法,具有一定的优势。Based on optical fiber laser in the network surge mutation data optimization scheduling design, realization of optical fiber laser is the accurate monitoring of the network. Traditional method USES the linear time series prediction method for surge mutation data scheduling, no surge in optical fiber laser can effectively mining network mutation nonlinear characteristics of data, the accuracy of the result in scheduling is bad. Based on nonlinear autocorrelation characteristics of recursive map matching and quantitative analysis of optical fiber laser in the network surge mutation data scheduling method, nonlinear time series analysis, the data of the surge mutation based on autocorrelation characteristic extracting quantitative reeursive analysis, extracting surge in recursive map mutation regularity characteristics of data, swell mutation data optimization scheduling. Simulation results show that the improved method for optical fiber laser network surge mutation data scheduling, the accuracy of scheduling and scheduling performance is superior to traditional methods, has a certain advantage.
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