农村建筑物作为地震灾害中最重要的承灾对象,对其类型、分布等信息的快速获取在抗震减灾等方面具有重要意义。基于GF-2高分辨率遥感数据,利用ESP(Estimation of Scale Parameter)算法和SeaTH(Seperability and Thresholds)算法分别确定...农村建筑物作为地震灾害中最重要的承灾对象,对其类型、分布等信息的快速获取在抗震减灾等方面具有重要意义。基于GF-2高分辨率遥感数据,利用ESP(Estimation of Scale Parameter)算法和SeaTH(Seperability and Thresholds)算法分别确定影像最佳分割尺度及构建最优特征学习空间,选用决策树分类法和随机森林机器学习分类法,分别对2021年5月初甘肃省襄南镇的农村建筑物结构进行提取分类,并使用无人机航测和现场调查统计数据进行分类结果的准确度检验和修正。结果表明:①两种方法都能较好地识别空间分布均匀、面积大、颜色鲜明的砖混建筑物,但对于分布杂乱且相对集中、颜色灰暗、面积小的土木(砖木)建筑物难以有效识别出其边界轮廓并准确分类。②两种方法对研究区建筑物分类的精度分别是82.42%、86.82%,且基于随机森林的方法在提取建筑物信息时出现的错分漏分现象较少,因此,随机森林方法进行农村建筑物分类更适用。展开更多
针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(R...针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(Remote Radio Head,RRH)选择、子载波分配和RRH功率分配三个维度进行研究。首先,根据传统的C-RAN系统传输模型和QoS约束在时变业务环境下建立了以发射功率为变量,以吞吐量最大为优化目标的优化问题;然后,基于改进的遗传算法,将原优化方案转变为通过优化RRH选择、子载波分配和RRH功率分配来达到提高系统吞吐量的目的;最后,将改进的遗传算法与其他智能算法在种群规模变化下进行了时间复杂度对比。实验结果表明,所提算法具有较低时间复杂度,所提资源分配方案下的平均吞吐量增益为17%。展开更多
In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset m...In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset mesh technique was used for mesh generation. RANS method was used to calculate the total resistance of the hull. In order to improve the efficiency and smoothness of the geometric reconstruction, the arbitrary shape deformation （ASD） technique was introduced to change the shape of the bulbous bow. To improve the global search ability of the particle swarm optimization （PSO） algorithm, an improved particle swarm optimization （IPSO） algorithm was proposed to set up the optimization model. After a series of optimization analyses, the optimal hull form was found. It can be concluded that the simulation based design framework built in this paper is a promising method for bulbous bow optimization.展开更多
文摘农村建筑物作为地震灾害中最重要的承灾对象,对其类型、分布等信息的快速获取在抗震减灾等方面具有重要意义。基于GF-2高分辨率遥感数据,利用ESP(Estimation of Scale Parameter)算法和SeaTH(Seperability and Thresholds)算法分别确定影像最佳分割尺度及构建最优特征学习空间,选用决策树分类法和随机森林机器学习分类法,分别对2021年5月初甘肃省襄南镇的农村建筑物结构进行提取分类,并使用无人机航测和现场调查统计数据进行分类结果的准确度检验和修正。结果表明:①两种方法都能较好地识别空间分布均匀、面积大、颜色鲜明的砖混建筑物,但对于分布杂乱且相对集中、颜色灰暗、面积小的土木(砖木)建筑物难以有效识别出其边界轮廓并准确分类。②两种方法对研究区建筑物分类的精度分别是82.42%、86.82%,且基于随机森林的方法在提取建筑物信息时出现的错分漏分现象较少,因此,随机森林方法进行农村建筑物分类更适用。
文摘针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(Remote Radio Head,RRH)选择、子载波分配和RRH功率分配三个维度进行研究。首先,根据传统的C-RAN系统传输模型和QoS约束在时变业务环境下建立了以发射功率为变量,以吞吐量最大为优化目标的优化问题;然后,基于改进的遗传算法,将原优化方案转变为通过优化RRH选择、子载波分配和RRH功率分配来达到提高系统吞吐量的目的;最后,将改进的遗传算法与其他智能算法在种群规模变化下进行了时间复杂度对比。实验结果表明,所提算法具有较低时间复杂度,所提资源分配方案下的平均吞吐量增益为17%。
基金financially supported by the National Natural Science Foundation of China(Grant No.51009087)the National Science Foundation of Shanghai(Grant No.14ZR1419500)
文摘In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset mesh technique was used for mesh generation. RANS method was used to calculate the total resistance of the hull. In order to improve the efficiency and smoothness of the geometric reconstruction, the arbitrary shape deformation （ASD） technique was introduced to change the shape of the bulbous bow. To improve the global search ability of the particle swarm optimization （PSO） algorithm, an improved particle swarm optimization （IPSO） algorithm was proposed to set up the optimization model. After a series of optimization analyses, the optimal hull form was found. It can be concluded that the simulation based design framework built in this paper is a promising method for bulbous bow optimization.
基金This work is supported by the National Natural Science Foundation of China （No. 60672059 and No. 60496315） and the National High Technology Research and Development Program of China （No. 2006AA01 Z233）.
