According to the railway transportation system＇s characteristics, a new cellular automaton model for the single- line railway system is presented in this paper. Based on this model, several simulations were done to i...According to the railway transportation system＇s characteristics, a new cellular automaton model for the single- line railway system is presented in this paper. Based on this model, several simulations were done to imitate the train operation under three working diagrams. From a different angle the results show how the organization of train operation impacts on the railway carrying capacity. By using the non-parallel train working diagram the influence of fast-train on slow-train is found to be the strongest. Many slow-trains have to wait in-between neighbouring stations to let the fast-train（s） pass through first. So the slow-train will advance like a wave propagating from the departure station to the arrival station. This also resembles the situation of a highway jammed traffic flow. Furthermore, the nonuniformity of travel times between the sections also greatly limits the railway carrying capacity. After converting the nonuniform sections into the sections with uniform travel times while the total travel time is kept unchanged, all three carrying capacities are improved greatly as shown by simulation. It also shows that the cellular automaton model is an effective and feasible way to investigate the railway transportation system.展开更多
为提升电力系统的自动配置能力,简化单线图操作过程,实现配网智能化调度,设计了图模数据解析下的配网单线图一键成图支持算法。以CIM(Common Information Model)模型为数据源,采用改进的肖维涅算法优化CIM数据质量,进行配网拓扑数据预处...为提升电力系统的自动配置能力,简化单线图操作过程,实现配网智能化调度,设计了图模数据解析下的配网单线图一键成图支持算法。以CIM(Common Information Model)模型为数据源,采用改进的肖维涅算法优化CIM数据质量,进行配网拓扑数据预处理,挖掘其所具有的关联性;通过转化拓扑关系形成特定树形,构建基于迭代二叉树3代算法的决策树机器学习模型,实现树节点坐标的自动分配;根据树边两端点坐标和该树边描述的设备种类,绘制矢量图形,简化单线图的操作过程。实验结果表明,该算法可有效提升配网图形的信息交互效果与电力系统自动配置能力,支持配网单线图一键成图功能。展开更多
文摘According to the railway transportation system＇s characteristics, a new cellular automaton model for the single- line railway system is presented in this paper. Based on this model, several simulations were done to imitate the train operation under three working diagrams. From a different angle the results show how the organization of train operation impacts on the railway carrying capacity. By using the non-parallel train working diagram the influence of fast-train on slow-train is found to be the strongest. Many slow-trains have to wait in-between neighbouring stations to let the fast-train（s） pass through first. So the slow-train will advance like a wave propagating from the departure station to the arrival station. This also resembles the situation of a highway jammed traffic flow. Furthermore, the nonuniformity of travel times between the sections also greatly limits the railway carrying capacity. After converting the nonuniform sections into the sections with uniform travel times while the total travel time is kept unchanged, all three carrying capacities are improved greatly as shown by simulation. It also shows that the cellular automaton model is an effective and feasible way to investigate the railway transportation system.
文摘为提升电力系统的自动配置能力,简化单线图操作过程,实现配网智能化调度,设计了图模数据解析下的配网单线图一键成图支持算法。以CIM(Common Information Model)模型为数据源,采用改进的肖维涅算法优化CIM数据质量,进行配网拓扑数据预处理,挖掘其所具有的关联性;通过转化拓扑关系形成特定树形,构建基于迭代二叉树3代算法的决策树机器学习模型,实现树节点坐标的自动分配;根据树边两端点坐标和该树边描述的设备种类,绘制矢量图形,简化单线图的操作过程。实验结果表明,该算法可有效提升配网图形的信息交互效果与电力系统自动配置能力,支持配网单线图一键成图功能。
