High-resolution sub-meter satellite data play an increasingly crucial role in the 3D real-scene China construction initiative.Current research on 3D reconstruction using high-resolution satellite data primarily focuse...High-resolution sub-meter satellite data play an increasingly crucial role in the 3D real-scene China construction initiative.Current research on 3D reconstruction using high-resolution satellite data primarily focuses on two approaches:Multi-stereo fusion and multi-view matching.While algorithms based on these two methodologies for multi-view image 3D reconstruction have reached relative maturity,no systematic comparison has been conducted specifically on satellite data to evaluate the relative merits of multi-stereo fusion versus multi-view matching methods.This paper conducts a comparative analysis of the practical accuracy of both approaches using high-resolution satellite datasets from diverse geographical regions.To ensure fairness in accuracy comparison,both methodologies employ non-local dense matching for cost optimization.Results demonstrate that the multi-stereo fusion method outperforms multi-view matching in all evaluation metrics,exhibiting approximately 1.2%higher average matching accuracy and 10.7%superior elevation precision in the experimental datasets.Therefore,for 3D modeling applications using satellite data,we recommend adopting the multi-stereo fusion approach for digital surface model(DSM)product generation.展开更多
针对设备故障和人为干扰等因素造成光伏数据缺失的问题,提出了一种基于生成对抗网络和纵横交叉粒子群算法的光伏数据缺失重构方法。首先,使用Wasserstein散度生成对抗网络(Wasserstein divergence for GANs,WGAN-div)学习光伏数据的时...针对设备故障和人为干扰等因素造成光伏数据缺失的问题,提出了一种基于生成对抗网络和纵横交叉粒子群算法的光伏数据缺失重构方法。首先,使用Wasserstein散度生成对抗网络(Wasserstein divergence for GANs,WGAN-div)学习光伏数据的时序性规律与耦合关系;其次,设计了重构约束,通过优化生成器的噪声输入,使得重构后的样本最大限度贴近真实样本;针对优化高维变量问题,采用纵横交叉算法催化粒子群算法的寻优过程,防止优化时出现早熟问题。实验结果表明,在光伏数据含有大量缺失值时,所提方法具有较高的重构准确率。该方法也适用于电力系统中类似数据的缺失值重构,具有良好的应用前景。展开更多
为了更好地抵制网络能量快速消耗和降低不可靠链路对无线传感器网络系统数据收集的影响以提高数据重构精度,提出了一种基于能量有效的多参数数据重构方法(Multi-parameter Data Reconstruction Method based on Energy Efficient,MDR)...为了更好地抵制网络能量快速消耗和降低不可靠链路对无线传感器网络系统数据收集的影响以提高数据重构精度,提出了一种基于能量有效的多参数数据重构方法(Multi-parameter Data Reconstruction Method based on Energy Efficient,MDR)。利用移动智能计算给出传感器节点之间多跳函数关系以确定传感器节点之间比例关系;通过稀疏矩阵设计一种低相干性的观测矩阵,抑制数据丢包率对整个传感网系统的影响,提高汇聚节点数据重构精度;通过基于数据转发策略确认机制实现簇间数据传输的高可靠性,完成了节点间多路径路由数据的可靠交付。仿真实验表明,在数据丢包率为40%的情况下,MDR的数据重构精度误差仍小于5%;在与其他算法比对时,其数据转发次数降低了10.36%,平均网络能耗降低了13.29%,从而验证了该算法的有效性和实效性。展开更多
文摘High-resolution sub-meter satellite data play an increasingly crucial role in the 3D real-scene China construction initiative.Current research on 3D reconstruction using high-resolution satellite data primarily focuses on two approaches:Multi-stereo fusion and multi-view matching.While algorithms based on these two methodologies for multi-view image 3D reconstruction have reached relative maturity,no systematic comparison has been conducted specifically on satellite data to evaluate the relative merits of multi-stereo fusion versus multi-view matching methods.This paper conducts a comparative analysis of the practical accuracy of both approaches using high-resolution satellite datasets from diverse geographical regions.To ensure fairness in accuracy comparison,both methodologies employ non-local dense matching for cost optimization.Results demonstrate that the multi-stereo fusion method outperforms multi-view matching in all evaluation metrics,exhibiting approximately 1.2%higher average matching accuracy and 10.7%superior elevation precision in the experimental datasets.Therefore,for 3D modeling applications using satellite data,we recommend adopting the multi-stereo fusion approach for digital surface model(DSM)product generation.
文摘针对设备故障和人为干扰等因素造成光伏数据缺失的问题,提出了一种基于生成对抗网络和纵横交叉粒子群算法的光伏数据缺失重构方法。首先,使用Wasserstein散度生成对抗网络(Wasserstein divergence for GANs,WGAN-div)学习光伏数据的时序性规律与耦合关系;其次,设计了重构约束,通过优化生成器的噪声输入,使得重构后的样本最大限度贴近真实样本;针对优化高维变量问题,采用纵横交叉算法催化粒子群算法的寻优过程,防止优化时出现早熟问题。实验结果表明,在光伏数据含有大量缺失值时,所提方法具有较高的重构准确率。该方法也适用于电力系统中类似数据的缺失值重构,具有良好的应用前景。
文摘为了更好地抵制网络能量快速消耗和降低不可靠链路对无线传感器网络系统数据收集的影响以提高数据重构精度,提出了一种基于能量有效的多参数数据重构方法(Multi-parameter Data Reconstruction Method based on Energy Efficient,MDR)。利用移动智能计算给出传感器节点之间多跳函数关系以确定传感器节点之间比例关系;通过稀疏矩阵设计一种低相干性的观测矩阵,抑制数据丢包率对整个传感网系统的影响,提高汇聚节点数据重构精度;通过基于数据转发策略确认机制实现簇间数据传输的高可靠性,完成了节点间多路径路由数据的可靠交付。仿真实验表明,在数据丢包率为40%的情况下,MDR的数据重构精度误差仍小于5%;在与其他算法比对时,其数据转发次数降低了10.36%,平均网络能耗降低了13.29%,从而验证了该算法的有效性和实效性。
