光网络的光通路状态实时感知研究

为提高光通路状态感知的实时性,提出了一种光网络的光通路状态实时感知方法。首先对光通路态势要素进行提取,然后对提取出的态势要素进行量化处理,最后采用神经网络的方法对光网络的光通路状态进一步感知,以此完成光网络的光通路状态实时感知。实验结果表明,此次研究的光网络的光通路状态实时感知方法不仅减少了光通路状态获取时间,保持在2 min内,还减少了随机异常事件定位时间,仅为0.75 min,并提高了随机异常事件定位准确性,达到91%,满足光网络的光通路状态实时感知方法的设计需求。

用集合思想处理计数问题

计数问题难在构造不重不漏的计数框架(程序),这里,集合思想可发挥作用．例1 如图1所示的一个5×4×4的长方体, 上面有2×1×4,2×1×5,3×1×4穿透的三个洞, 那么剩下部分的体积是( )

片上系统高层等价性检验研究进展

针对近年来SoC领域的工作,首先分析了高层等价性检验的难点;然后从算法类型归类角度对各种高层等价性检验方法进行了概述评论,同时分析了各类算法的优缺点和现有算法的主要技术手段;最后讨论了SoC高层等价性检验方法目前面临的挑战,并对该领域今后的研究方向进行了展望.

Travel time prediction model of freeway based on gradient boosting decision tree

To investigate the travel time prediction method of the freeway, a model based on the gradient boosting decision tree (GBDT) is proposed. Eleven variables (namely, travel time in current period T i , traffic flow in current period Q i , speed in current period V i , density in current period K i , the number of vehicles in current period N i , occupancy in current period R i , traffic state parameter in current period X i , travel time in previous time period T i -1 , etc.) are selected to predict the travel time for 10 min ahead in the proposed model. Data obtained from VISSIM simulation is used to train and test the model. The results demonstrate that the prediction error of the GBDT model is smaller than those of the back propagation (BP) neural network model and the support vector machine (SVM) model. Travel time in current period T i is the most important variable among all variables in the GBDT model. The GBDT model can produce more accurate prediction results and mine the hidden nonlinear relationships deeply between variables and the predicted travel time.

OTN智能光网络关键技术研究

以OTN为代表的新一代光传送技术逐渐成为光传送网的主流,主要对OTN智能光网络的光通路路由状态监测技术、智能控制平面技术、多业务透明映射技术光纤选择、传输技术、光放大技术、波长变换技术、OTN生存性技术、OTN管理技术这10种关键技术进行分析和研究,最后做出总结。

SoC高级综合验证研究进展

针对近年来片上系统(system on chip,SoC)高级综合验证领域的工作,首先分析了高级综合验证的难点,然后根据应用领域将算法分为3类:高级综合前端验证算法、高级综合调度验证算法和高级综合后端验证算法.同时分析了各类算法的优缺点和现有算法的主要技术手段;最后讨论了SoC高级综合验证算法目前面临的映射关系缺失、状态空间爆炸和复杂的数据结构等挑战,并对该领域今后的研究方向进行了展望.

A simple channel estimator for space-time coded OFDM systems in rapid fading channels

A simple channel estimator for space-time coded orthogonal frequency division multiplexing (OFDM) systems in rapid fading channels is proposed. The channels at the training bauds are estimated using the EM (expectation-maximization) algorithm, while the channels at the data bauds are estimated based on the method for modelling the time-varying channel as the linear combination of several time-invariant " Doppler channels". Computer simulations showed that this estimator outperforms the decision-directed tracking in rapid fading channels and that the performance of this method can be improved by iteration.

Virtual speed sensors based algorithm for expressway traffic state estimation

The accurate estimation of expressway traffic state can provide decision-making for both travelers and traffic managers. The speed is one of the most representative parameter of the traffic state. So the expressway speed spatial distribution can be taken as the expressway traffic state equivalent. In this paper, an algorithm based on virtual speed sensors (VSS) is presented to estimate the expressway traffic state (the speed spatial distribution). To gain the spatial distribution of expressway traffic state, virtual speed sensors are defined between adjacent traffic flow sensors. Then, the speed data extracted from traffic flow sensors in time series are mapped to space series to design virtual speed sensors. Then the speed of virtual speed sensors can be calculated with the weight matrix which is related with the speed of virtual speed sensors and the speed data extracted from traffic flow sensors and the speed data extracted from traffic flow sensors in time series. Finally, the expressway traffic state (the speed spatial distribution) can be gained. The acquisition of average travel speed of the expressway is taken for application of this traffic state estimation algorithm. One typical expressway in Beijing is adopted for the experiment analysis. The results prove that this traffic state estimation approach based on VSS is feasible and can achieve a high accuracy.

基于OTN技术下智能光网络相关技术研究

近些年来网络通讯技术不断的更新升级,其发展前景也越来越广。但在通信技术发展的过程中也会遇到一些问题,例如当前的相关技术发展的还不太完善,通讯速度以及信号质量还有待提高等,对于这些问题经过研究人员不断的努力,最终研发出了OTN技术,该技术也逐渐成为传输网组网技术中的一部分。OTN技术主要是为了实现全光组网,在通信网络内部进行合理地调整。本文主要在我国通信智能光网络技术发展现状的基础上,进一步对OTN技术在智能网络中的应用进行研究,主要从该技术的检测、智能控制平面技术、OTN交叉技术的角度出发进行深入研究,不断促进我国网络通信技术的发展。