With the rapid development of low-orbit satellite com-munication networks both domestically and internationally,space-terrestrial integrated networks will become the future development trend.For space and terrestrial ...With the rapid development of low-orbit satellite com-munication networks both domestically and internationally,space-terrestrial integrated networks will become the future development trend.For space and terrestrial networks with limi-ted resources,the utilization efficiency of the entire space-terres-trial integrated networks resources can be affected by the core network indirectly.In order to improve the response efficiency of core networks expansion construction,early warning of the core network elements capacity is necessary.Based on the inte-grated architecture of space and terrestrial network,multidimen-sional factors are considered in this paper,including the number of terminals,login users,and the rules of users’migration during holidays.Using artifical intelligence(AI)technologies,the regis-tered users of the access and mobility management function(AMF),authorization users of the unified data management(UDM),protocol data unit(PDU)sessions of session manage-ment function(SMF)are predicted in combination with the num-ber of login users,the number of terminals.Therefore,the core network elements capacity can be predicted in advance.The proposed method is proven to be effective based on the data from real network.展开更多
针对城市重要公交线路识别与优化问题,以西安市公交系统作为研究对象,利用高阶网络模型甄别和优化西安市公交系统的重要公交线路.首先,考虑到城市公交系统具有典型的路径依赖特征,基于高阶网络模型方法构建高阶公交网络.其次,基于公交...针对城市重要公交线路识别与优化问题,以西安市公交系统作为研究对象,利用高阶网络模型甄别和优化西安市公交系统的重要公交线路.首先,考虑到城市公交系统具有典型的路径依赖特征,基于高阶网络模型方法构建高阶公交网络.其次,基于公交站点道路等级、站点与轨道交通接驳情况、站点服务范围内兴趣点(Point of Interest,POI)、站点所在区域的人口密度4项位置属性指标,提出改进的加权k核分解算法,将高阶公交网络分为核心层、桥层和外围层.最后,以西安市为例进行实证分析,以各层中连边承担的平均线路数为依据甄别重要公交线路,并根据路段在重要连边中出现的次数识别出最重要的公交路段,针对存在的问题提出优化建议.研究结果表明:西安市公交系统中存在234条重要的公交路段以及经过6条最重要路段的55条公交线路;西安市存在城市新区及近郊区域与中心城区连接不畅的问题,桥层中有524个公交站点与核心层中的任意一个站点都没有直达的公交线路;通过对13条非直达线路进行优化,站点直达率提高4.72%,增加了13条线路中247个站点与核心层站点的直达路线选择,改善了城市居民的出行便利性.展开更多
以鄂尔多斯盆地某区块的砂泥夹层岩心为研究对象,使用基于小波变换的去噪神经网络(denoising neural network based on wavelet transformation,DWTNet)对于岩心的图像进行去噪研究。该方法的评断结果采用峰值信噪比(peak signal to noi...以鄂尔多斯盆地某区块的砂泥夹层岩心为研究对象,使用基于小波变换的去噪神经网络(denoising neural network based on wavelet transformation,DWTNet)对于岩心的图像进行去噪研究。该方法的评断结果采用峰值信噪比(peak signal to noise ratio,PSNR)和去噪后的图像结果进行了对比。研究表明,利用DWTNet在测试集YX1、YX2测试所提出的算法,并与EGDNet等去噪算法进行对比,PSNR在噪声为25、50、75 dB时,高于EGDNet算法0.527、0.418、1.1 dB。所提的算法在峰值信噪比等指标均高于其他算法;并在视觉效果上其处理得到的图像也更加清晰。方法的提出对于孔隙度、平均体积比表面积、平均曲率计算等都有着非常重要的意义。展开更多
基金This work was supported by the National Key Research Plan(2021YFB2900602).
文摘With the rapid development of low-orbit satellite com-munication networks both domestically and internationally,space-terrestrial integrated networks will become the future development trend.For space and terrestrial networks with limi-ted resources,the utilization efficiency of the entire space-terres-trial integrated networks resources can be affected by the core network indirectly.In order to improve the response efficiency of core networks expansion construction,early warning of the core network elements capacity is necessary.Based on the inte-grated architecture of space and terrestrial network,multidimen-sional factors are considered in this paper,including the number of terminals,login users,and the rules of users’migration during holidays.Using artifical intelligence(AI)technologies,the regis-tered users of the access and mobility management function(AMF),authorization users of the unified data management(UDM),protocol data unit(PDU)sessions of session manage-ment function(SMF)are predicted in combination with the num-ber of login users,the number of terminals.Therefore,the core network elements capacity can be predicted in advance.The proposed method is proven to be effective based on the data from real network.
文摘针对城市重要公交线路识别与优化问题,以西安市公交系统作为研究对象,利用高阶网络模型甄别和优化西安市公交系统的重要公交线路.首先,考虑到城市公交系统具有典型的路径依赖特征,基于高阶网络模型方法构建高阶公交网络.其次,基于公交站点道路等级、站点与轨道交通接驳情况、站点服务范围内兴趣点(Point of Interest,POI)、站点所在区域的人口密度4项位置属性指标,提出改进的加权k核分解算法,将高阶公交网络分为核心层、桥层和外围层.最后,以西安市为例进行实证分析,以各层中连边承担的平均线路数为依据甄别重要公交线路,并根据路段在重要连边中出现的次数识别出最重要的公交路段,针对存在的问题提出优化建议.研究结果表明:西安市公交系统中存在234条重要的公交路段以及经过6条最重要路段的55条公交线路;西安市存在城市新区及近郊区域与中心城区连接不畅的问题,桥层中有524个公交站点与核心层中的任意一个站点都没有直达的公交线路;通过对13条非直达线路进行优化,站点直达率提高4.72%,增加了13条线路中247个站点与核心层站点的直达路线选择,改善了城市居民的出行便利性.
文摘以鄂尔多斯盆地某区块的砂泥夹层岩心为研究对象,使用基于小波变换的去噪神经网络(denoising neural network based on wavelet transformation,DWTNet)对于岩心的图像进行去噪研究。该方法的评断结果采用峰值信噪比(peak signal to noise ratio,PSNR)和去噪后的图像结果进行了对比。研究表明,利用DWTNet在测试集YX1、YX2测试所提出的算法,并与EGDNet等去噪算法进行对比,PSNR在噪声为25、50、75 dB时,高于EGDNet算法0.527、0.418、1.1 dB。所提的算法在峰值信噪比等指标均高于其他算法;并在视觉效果上其处理得到的图像也更加清晰。方法的提出对于孔隙度、平均体积比表面积、平均曲率计算等都有着非常重要的意义。
