针对在安全条件下输电线路的最大载流量计算问题,提出一种基于气象数值网格点预报产品的输电线路最大载流量预测值计算方法。该方法首先使用中尺度WRF（weather research and forecasting model）模式输出的气象数值预报网格点映射长距...针对在安全条件下输电线路的最大载流量计算问题,提出一种基于气象数值网格点预报产品的输电线路最大载流量预测值计算方法。该方法首先使用中尺度WRF（weather research and forecasting model）模式输出的气象数值预报网格点映射长距离输电线路计算基准点的1~36 h环境预报值,然后利用输电线路热平衡方程计算线路计算基准点最大载流量预测值,并推出整条线路最大载流量预测值,实现了长距离输电线路1-36 h最大载流量预测值的计算。计算结果表明,在完全满足输电线路安全条件下,使用该方法调度的输电线路载流容量将比日常调度载流容量有大幅度提高,即使是在全年最高峰的负载条件下,该方法也有30%左右的优化空间,有效解决了输电线路安全增容、电网优化调度策略等难题。该方法同时具有预测时间粒度小、预见期长、可适用跨区域大范围电网等特点。展开更多
Let G be a connected graph of order n and m_(RD)^(L)_(G)I denote the number of reciprocal distance Laplacian eigenvaluesof G in an interval I.For a given interval I,we mainly present several bounds on m_(RD)^(L)_(G)I ...Let G be a connected graph of order n and m_(RD)^(L)_(G)I denote the number of reciprocal distance Laplacian eigenvaluesof G in an interval I.For a given interval I,we mainly present several bounds on m_(RD)^(L)_(G)I in terms of various structuralparameters of the graph G,including vertex-connectivity,independence number and pendant vertices.展开更多
In order to forecast projectile impact points quickly and accurately,aprojectile impact point prediction method based on generalized regression neural network（GRNN）is presented.Firstly,the model of GRNN forecasting ...In order to forecast projectile impact points quickly and accurately,aprojectile impact point prediction method based on generalized regression neural network（GRNN）is presented.Firstly,the model of GRNN forecasting impact point is established;secondly,the particle swarm algorithm（PSD）is used to optimize the smooth factor in the prediction model and then the optimal GRNN impact point prediction model is obtained.Finally,the numerical simulation of this prediction model is carried out.Simulation results show that the maximum range error is no more than 40 m,and the lateral deviation error is less than0.2m.The average time of impact point prediction is 6.645 ms,which is 1 300.623 ms less than that of numerical integration method.Therefore,it is feasible and effective for the proposed method to forecast projectile impact points,and thus it can provide a theoretical reference for practical engineering applications.展开更多
In this paper we consider the extreme points of closed convex hull of the class T σ(p,α) and then it is used to determine the coefficient bounds. Some other interesting properties of the class T σ(p,α) are also...In this paper we consider the extreme points of closed convex hull of the class T σ(p,α) and then it is used to determine the coefficient bounds. Some other interesting properties of the class T σ(p,α) are also investigated.展开更多
文摘针对在安全条件下输电线路的最大载流量计算问题,提出一种基于气象数值网格点预报产品的输电线路最大载流量预测值计算方法。该方法首先使用中尺度WRF（weather research and forecasting model）模式输出的气象数值预报网格点映射长距离输电线路计算基准点的1~36 h环境预报值,然后利用输电线路热平衡方程计算线路计算基准点最大载流量预测值,并推出整条线路最大载流量预测值,实现了长距离输电线路1-36 h最大载流量预测值的计算。计算结果表明,在完全满足输电线路安全条件下,使用该方法调度的输电线路载流容量将比日常调度载流容量有大幅度提高,即使是在全年最高峰的负载条件下,该方法也有30%左右的优化空间,有效解决了输电线路安全增容、电网优化调度策略等难题。该方法同时具有预测时间粒度小、预见期长、可适用跨区域大范围电网等特点。
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region of China“Graph problems of topological parameters based on the spectra of graph matrices”(2021D01C069)the National Natural Science Foundation of the People's Republic of China“The investigation of spectral properties of graph operations and their related problems”(12161085)。
文摘Let G be a connected graph of order n and m_(RD)^(L)_(G)I denote the number of reciprocal distance Laplacian eigenvaluesof G in an interval I.For a given interval I,we mainly present several bounds on m_(RD)^(L)_(G)I in terms of various structuralparameters of the graph G,including vertex-connectivity,independence number and pendant vertices.
基金Project Funded by Chongqing Changjiang Electrical Appliances Industries Group Co.,Ltd
文摘In order to forecast projectile impact points quickly and accurately,aprojectile impact point prediction method based on generalized regression neural network（GRNN）is presented.Firstly,the model of GRNN forecasting impact point is established;secondly,the particle swarm algorithm（PSD）is used to optimize the smooth factor in the prediction model and then the optimal GRNN impact point prediction model is obtained.Finally,the numerical simulation of this prediction model is carried out.Simulation results show that the maximum range error is no more than 40 m,and the lateral deviation error is less than0.2m.The average time of impact point prediction is 6.645 ms,which is 1 300.623 ms less than that of numerical integration method.Therefore,it is feasible and effective for the proposed method to forecast projectile impact points,and thus it can provide a theoretical reference for practical engineering applications.
文摘In this paper we consider the extreme points of closed convex hull of the class T σ(p,α) and then it is used to determine the coefficient bounds. Some other interesting properties of the class T σ(p,α) are also investigated.
