To improve the performance of Ad hoc on-demand multipath distance vector (AOMDV) protocol, we proposed NS-AOMDV which is short for “AOMDV based on node state”. In NS-AOMDV, we introduce node state to improve AOMDV’...To improve the performance of Ad hoc on-demand multipath distance vector (AOMDV) protocol, we proposed NS-AOMDV which is short for “AOMDV based on node state”. In NS-AOMDV, we introduce node state to improve AOMDV’s performance in selecting main path. In route discovery process, the routing update rule calculates the node weight of each path and sorts the path weight by descending value in route list, and we choose the path which has the largest path weight for data transmission. NS-AOMDV also uses the technology of route request (RREQ) packet delay forwarding and energy threshold to ease network congestion, limit the RREQ broadcast storm, and avoid low energy nodes to participate in the establishment of the path. The results of simulation show that NS-AOMDV can effectively improve the networks’packets delivery rate, throughput and normalized routing overhead in the situation of dynamic network topology and heavy load.展开更多
With the goal of achieving advanced and multi-step prediction of silicon content of molten iron in the blast furnace ironmaking process,a path adaptive optimization seeking strategy coupled with simulated annealing al...With the goal of achieving advanced and multi-step prediction of silicon content of molten iron in the blast furnace ironmaking process,a path adaptive optimization seeking strategy coupled with simulated annealing algorithm and genetic algorithm was proposed from the perspective of innovative intelligent algorithm application.It was further coupled with wavelet neural network algorithm to deeply explore the nonlinear and strong coupling relationship between the information of big data samples and construct a cascade model for continuous prediction of silicon content of molten iron with the intelligent research results of state variables such as permeability index as the node and silicon content forecast as the output.In the model construction process,the 3r criterion was used for non-anomaly estimation of abnormal data to build a time-aligned sample set for multi-step forecasting of iron content,the normalization method was used to eliminate the influence of dimensionality of sample information,and the spearman correlation analysis algorithm was used to eliminate the time delay between state variables,control variables,and silicon content of molten iron in the blast furnace smelting process.The results show that permeability and theoretical combustion temperature as the key state variable nodes have real-time correlation with the silicon content of molten iron,and there are accurate forecasting results on the optimal path with the endpoint of molten iron silicon content prediction.The path finding based on the improved genetic algorithm of simulated annealing has good effect on the downscaling and depth characterization of sample data and improves the data ecology for the application of wavelet neural network algorithm.The accuracy of the real-time continuous forecasting model for the silicon content of molten iron reaches 95.24%;the hit rate of continuous forecasting one step ahead reaches 91.16%,and the hit rate of continuous forecasting five steps ahead is 87.41%.This model,which can realize the nodal dynamics of state variables,has better promotion value.展开更多
Classical network reliability problems assume both net- works and components have only binary states, fully working or fully failed states. But many actual networks are multi-state, such as communication networks and ...Classical network reliability problems assume both net- works and components have only binary states, fully working or fully failed states. But many actual networks are multi-state, such as communication networks and transportation networks. The nodes and arcs in the networks may be in intermediate states which are not fully working either fully failed. A simulation ap- proach for computing the two-terminal reliability of a multi-state network is described. Two-terminal reliability is defined as the probability that d units of demand can be supplied from the source to sink nodes under the time threshold T. The capacities of arcs may be in a stochastic state following any discrete or continuous distribution. The transmission time of each arc is also not a fixed number but stochastic according to its current capacity and de- mand. To solve this problem, a capacitated stochastic coloured Petri net is proposed for modelling the system behaviour. Places and transitions respectively stand for the nodes and arcs of a net- work. Capacitated transition and self-modified token colour with route information are defined to describe the multi-state network. By the simulation, the two-terminal reliability and node importance can be estimated and the optimal route whose reliability is highest can also be given. Finally, two examples of different kinds of multi- state networks are given.展开更多
In the paper the simplified criterion of a steady-state stability of electric power systems (EPS) is justified on the basis of Lyapunov functions in a quadratic form ensuring necessary and sufficient conditions of its...In the paper the simplified criterion of a steady-state stability of electric power systems (EPS) is justified on the basis of Lyapunov functions in a quadratic form ensuring necessary and sufficient conditions of its performance. Upon that, the use of the node-voltage equations allows reducing study of a steady-state stability of complex EPS to study of the generator-bus system. The obtained results facilitate studies of a steady-state stability of the complex systems and have practical importance.展开更多
Dirac semimetals are materials in which the conduction and the valence bands have robust crossing points protected by topology or symmetry. Recently, a new type of Dirac semimetals, so called the Dirac line-node semim...Dirac semimetals are materials in which the conduction and the valence bands have robust crossing points protected by topology or symmetry. Recently, a new type of Dirac semimetals, so called the Dirac line-node semimetals （DLNSs）, have attracted a lot of attention, as they host robust Dirac points along the one-dimensional （1D） lines in the Brillouin zone （BZ）. In this work, using angle-resolved photoemission spectroscopy （ARPES） and first-principles calculations, we systematically investigated the electronic structures of non-symmorphic ZrSiS crystal where we clearly distinguished the surface states from the bulk states. The photon-energy-dependent measurements further prove the existence of Dirac line node along the X-R direction. Remarkably, by in situ surface potassium doping, we clearly observed the different evolutions of the bulk and surface electronic states while proving the robustness of the Dirac line node. Our studies not only reveal the complete electronic structures of ZrSiS, but also demonstrate the method manipulating the electronic structure of the compound.展开更多
工业物联网(Industrial Internet of Things,IIoT)中通信故障具有突发性与结构依赖性,提升节点异常状态的预测精度对保障IIoT系统的稳定运行具有重要意义。文章构建了基于图神经网络(Graph Neural Network,GNN)的通信故障预测模型,提出...工业物联网(Industrial Internet of Things,IIoT)中通信故障具有突发性与结构依赖性,提升节点异常状态的预测精度对保障IIoT系统的稳定运行具有重要意义。文章构建了基于图神经网络(Graph Neural Network,GNN)的通信故障预测模型,提出了通信图建模方法。该方法设计了多层图卷积结构与注意力机制,构建了多类别故障标签并实现动态图序列预测。实验结果表明,该方法在预测准确率、故障识别能力与推理效率方面优于传统模型,可以有效感知节点间拓扑与状态演化关系,在工业通信网络中具备部署价值与应用前景。展开更多
无线传感器网络(WSNs)的运行效果对保证网络定位精度具有重要的意义。由于网络定位信息数据均可由自组网内节点随机获取,网络定位适用性在先验式路由协议链路状态路由协议(Optimized Link State Routing,OLSR)下表现更好。为了解决OLSR...无线传感器网络(WSNs)的运行效果对保证网络定位精度具有重要的意义。由于网络定位信息数据均可由自组网内节点随机获取,网络定位适用性在先验式路由协议链路状态路由协议(Optimized Link State Routing,OLSR)下表现更好。为了解决OLSR的多点中继(Multpoint Relays,MPR)节点运动速度较快的问题,为此设计了一种基于能量消耗的网络定位OLSR路由协议MPR机制评估方法,并开展仿真分析。研究结果表明:与原协议相比,节点能量消耗MPR选举生成协议表现出的性能更佳,经能量消耗MPR后形成的协议的吞吐量更大,有利于促进网络运行稳定性的提高。展开更多
文摘To improve the performance of Ad hoc on-demand multipath distance vector (AOMDV) protocol, we proposed NS-AOMDV which is short for “AOMDV based on node state”. In NS-AOMDV, we introduce node state to improve AOMDV’s performance in selecting main path. In route discovery process, the routing update rule calculates the node weight of each path and sorts the path weight by descending value in route list, and we choose the path which has the largest path weight for data transmission. NS-AOMDV also uses the technology of route request (RREQ) packet delay forwarding and energy threshold to ease network congestion, limit the RREQ broadcast storm, and avoid low energy nodes to participate in the establishment of the path. The results of simulation show that NS-AOMDV can effectively improve the networks’packets delivery rate, throughput and normalized routing overhead in the situation of dynamic network topology and heavy load.
基金financially supported by the National Natural Science Foundation of China(Grant No.52074126)Tangshan Science and Technology Plan Project(Grant No.22130201G).
文摘With the goal of achieving advanced and multi-step prediction of silicon content of molten iron in the blast furnace ironmaking process,a path adaptive optimization seeking strategy coupled with simulated annealing algorithm and genetic algorithm was proposed from the perspective of innovative intelligent algorithm application.It was further coupled with wavelet neural network algorithm to deeply explore the nonlinear and strong coupling relationship between the information of big data samples and construct a cascade model for continuous prediction of silicon content of molten iron with the intelligent research results of state variables such as permeability index as the node and silicon content forecast as the output.In the model construction process,the 3r criterion was used for non-anomaly estimation of abnormal data to build a time-aligned sample set for multi-step forecasting of iron content,the normalization method was used to eliminate the influence of dimensionality of sample information,and the spearman correlation analysis algorithm was used to eliminate the time delay between state variables,control variables,and silicon content of molten iron in the blast furnace smelting process.The results show that permeability and theoretical combustion temperature as the key state variable nodes have real-time correlation with the silicon content of molten iron,and there are accurate forecasting results on the optimal path with the endpoint of molten iron silicon content prediction.The path finding based on the improved genetic algorithm of simulated annealing has good effect on the downscaling and depth characterization of sample data and improves the data ecology for the application of wavelet neural network algorithm.The accuracy of the real-time continuous forecasting model for the silicon content of molten iron reaches 95.24%;the hit rate of continuous forecasting one step ahead reaches 91.16%,and the hit rate of continuous forecasting five steps ahead is 87.41%.This model,which can realize the nodal dynamics of state variables,has better promotion value.
基金supported by the National Natural Science Foundation of China (70971132)
文摘Classical network reliability problems assume both net- works and components have only binary states, fully working or fully failed states. But many actual networks are multi-state, such as communication networks and transportation networks. The nodes and arcs in the networks may be in intermediate states which are not fully working either fully failed. A simulation ap- proach for computing the two-terminal reliability of a multi-state network is described. Two-terminal reliability is defined as the probability that d units of demand can be supplied from the source to sink nodes under the time threshold T. The capacities of arcs may be in a stochastic state following any discrete or continuous distribution. The transmission time of each arc is also not a fixed number but stochastic according to its current capacity and de- mand. To solve this problem, a capacitated stochastic coloured Petri net is proposed for modelling the system behaviour. Places and transitions respectively stand for the nodes and arcs of a net- work. Capacitated transition and self-modified token colour with route information are defined to describe the multi-state network. By the simulation, the two-terminal reliability and node importance can be estimated and the optimal route whose reliability is highest can also be given. Finally, two examples of different kinds of multi- state networks are given.
文摘In the paper the simplified criterion of a steady-state stability of electric power systems (EPS) is justified on the basis of Lyapunov functions in a quadratic form ensuring necessary and sufficient conditions of its performance. Upon that, the use of the node-voltage equations allows reducing study of a steady-state stability of complex EPS to study of the generator-bus system. The obtained results facilitate studies of a steady-state stability of the complex systems and have practical importance.
基金Project supported by the National Key R&D Program of China(Grant No.2017YFA0305400)Chinese Academy of Science–Shanghai Science Research Center(Grant No.CAS-SSRC-YH-2015-01)+2 种基金the National Natural Science Foundation of China(Grant No.11674229)the Engineering and Physical Sciences Research Council Platform(Grant No.EP/M020517/1)the Hefei Science–Center Chinese Academy of Sciences(Grant No.2015HSC-UE013)
文摘Dirac semimetals are materials in which the conduction and the valence bands have robust crossing points protected by topology or symmetry. Recently, a new type of Dirac semimetals, so called the Dirac line-node semimetals （DLNSs）, have attracted a lot of attention, as they host robust Dirac points along the one-dimensional （1D） lines in the Brillouin zone （BZ）. In this work, using angle-resolved photoemission spectroscopy （ARPES） and first-principles calculations, we systematically investigated the electronic structures of non-symmorphic ZrSiS crystal where we clearly distinguished the surface states from the bulk states. The photon-energy-dependent measurements further prove the existence of Dirac line node along the X-R direction. Remarkably, by in situ surface potassium doping, we clearly observed the different evolutions of the bulk and surface electronic states while proving the robustness of the Dirac line node. Our studies not only reveal the complete electronic structures of ZrSiS, but also demonstrate the method manipulating the electronic structure of the compound.
文摘工业物联网(Industrial Internet of Things,IIoT)中通信故障具有突发性与结构依赖性,提升节点异常状态的预测精度对保障IIoT系统的稳定运行具有重要意义。文章构建了基于图神经网络(Graph Neural Network,GNN)的通信故障预测模型,提出了通信图建模方法。该方法设计了多层图卷积结构与注意力机制,构建了多类别故障标签并实现动态图序列预测。实验结果表明,该方法在预测准确率、故障识别能力与推理效率方面优于传统模型,可以有效感知节点间拓扑与状态演化关系,在工业通信网络中具备部署价值与应用前景。
文摘无线传感器网络(WSNs)的运行效果对保证网络定位精度具有重要的意义。由于网络定位信息数据均可由自组网内节点随机获取,网络定位适用性在先验式路由协议链路状态路由协议(Optimized Link State Routing,OLSR)下表现更好。为了解决OLSR的多点中继(Multpoint Relays,MPR)节点运动速度较快的问题,为此设计了一种基于能量消耗的网络定位OLSR路由协议MPR机制评估方法,并开展仿真分析。研究结果表明:与原协议相比,节点能量消耗MPR选举生成协议表现出的性能更佳,经能量消耗MPR后形成的协议的吞吐量更大,有利于促进网络运行稳定性的提高。
