Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets （POCS） based image restoration method into the seismic data...Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets （POCS） based image restoration method into the seismic data reconstruction field to interpolate irregularly missing traces. For entire dead traces, we transfer the POCS iteration reconstruction process from the time to frequency domain to save computational cost because forward and reverse Fourier time transforms are not needed. In each iteration, the selection threshold parameter is important for reconstruction efficiency. In this paper, we designed two types of threshold models to reconstruct irregularly missing seismic data. The experimental results show that an exponential threshold can greatly reduce iterations and improve reconstruction efficiency compared to a linear threshold for the same reconstruction result. We also analyze the anti- noise and anti-alias ability of the POCS reconstruction method. Finally, theoretical model tests and real data examples indicate that the proposed method is efficient and applicable.展开更多
Rhododendron is famous for its high ornamental value.However,the genus is taxonomically difficult and the relationships within Rhododendron remain unresolved.In addition,the origin of key morphological characters with...Rhododendron is famous for its high ornamental value.However,the genus is taxonomically difficult and the relationships within Rhododendron remain unresolved.In addition,the origin of key morphological characters with high horticulture value need to be explored.Both problems largely hinder utilization of germplasm resources.Most studies attempted to disentangle the phylogeny of Rhododendron,but only used a few genomic markers and lacked large-scale sampling,resulting in low clade support and contradictory phylogenetic signals.Here,we used restriction-site associated DNA sequencing(RAD-seq)data and morphological traits for 144 species of Rhododendron,representing all subgenera and most sections and subsections of this species-rich genus,to decipher its intricate evolutionary history and reconstruct ancestral state.Our results revealed high resolutions at subgenera and section levels of Rhododendron based on RAD-seq data.Both optimal phylogenetic tree and split tree recovered five lineages among Rhododendron.Subg.Therorhodion(cladeⅠ)formed the basal lineage.Subg.Tsutsusi and Azaleastrum formed cladeⅡand had sister relationships.CladeⅢincluded all scaly rhododendron species.Subg.Pentanthera(cladeⅣ)formed a sister group to Subg.Hymenanthes(cladeⅤ).The results of ancestral state reconstruction showed that Rhododendron ancestor was a deciduous woody plant with terminal inflorescence,ten stamens,leaf blade without scales and broadly funnelform corolla with pink or purple color.This study shows significant distinguishability to resolve the evolutionary history of Rhododendron based on high clade support of phylogenetic tree constructed by RAD-seq data.It also provides an example to resolve discordant signals in phylogenetic trees and demonstrates the application feasibility of RAD-seq with large amounts of missing data in deciphering intricate evolutionary relationships.Additionally,the reconstructed ancestral state of six important characters provides insights into the innovation of key characters in Rhododendron.展开更多
Precipitation is the most discontinuous atmospheric parameter because of its temporal and spatial variability. Precipitation observations at automatic weather stations（AWSs） show different patterns over different ti...Precipitation is the most discontinuous atmospheric parameter because of its temporal and spatial variability. Precipitation observations at automatic weather stations（AWSs） show different patterns over different time periods. This paper aims to reconstruct missing data by finding the time periods when precipitation patterns are similar, with a method called the intermittent sliding window period（ISWP） technique—a novel approach to reconstructing the majority of non-continuous missing real-time precipitation data. The ISWP technique is applied to a 1-yr precipitation dataset（January 2015 to January 2016）, with a temporal resolution of 1 h, collected at 11 AWSs run by the Indian Meteorological Department in the capital region of Delhi. The acquired dataset has missing precipitation data amounting to 13.66%, of which 90.6% are reconstructed successfully. Furthermore, some traditional estimation algorithms are applied to the reconstructed dataset to estimate the remaining missing values on an hourly basis. The results show that the interpolation of the reconstructed dataset using the ISWP technique exhibits high quality compared with interpolation of the raw dataset. By adopting the ISWP technique, the root-mean-square errors（RMSEs）in the estimation of missing rainfall data—based on the arithmetic mean, multiple linear regression, linear regression,and moving average methods—are reduced by 4.2%, 55.47%, 19.44%, and 9.64%, respectively. However, adopting the ISWP technique with the inverse distance weighted method increases the RMSE by 0.07%, due to the fact that the reconstructed data add a more diverse relation to its neighboring AWSs.展开更多
受到外业采集条件限制和施工环境的影响,通常很难采集到理想且完整的规则采样地质雷达数据。地质雷达数据的缺失和不规则采样容易对数据处理过程产生严重干扰,影响后续解释工作。本文给出了一种基于无展开随机QR分解(Uncoiled Randomize...受到外业采集条件限制和施工环境的影响,通常很难采集到理想且完整的规则采样地质雷达数据。地质雷达数据的缺失和不规则采样容易对数据处理过程产生严重干扰,影响后续解释工作。本文给出了一种基于无展开随机QR分解(Uncoiled Randomized QR decomposition,URQR)的地质雷达数据重建方法。首先引入随机QR分解算法实现对地质雷达数据矩阵的降秩计算,并通过利用无展开求平均快速算法,来解决降秩后的Toeplitz矩阵对角线求平均效率低,内存占用量大的问题。然后基于凸集投影理论,实现了无展开随机QR分解算法的数据重建流程。最后,利用本文方法与随机奇异值分解(Randomized Singular Value Decomposition,RSVD)算法,对理论与实际地质雷达缺失道数据进行重建,通过对比质量因子Q值,说明了本文方法重建效果优于RSVD方法,对于大型地质雷达数据的重建,本文方法计算效率明显高于RSVD方法,验证了本文方法的有效性、可行性、效率高的特点。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
针对化工过程数据中存在缺失数据的问题,在保持局部数据结构特征的基础上提出了基于局部加权重构的化工过程数据恢复算法。通过定位缺失的数据点并以符号Na N(Not a Number)标记,将缺失的数据集分为完备数据集和不完备数据集。不完备的...针对化工过程数据中存在缺失数据的问题,在保持局部数据结构特征的基础上提出了基于局部加权重构的化工过程数据恢复算法。通过定位缺失的数据点并以符号Na N(Not a Number)标记,将缺失的数据集分为完备数据集和不完备数据集。不完备的数据集按照完整性的大小依次找到它们在完备数据集中相应的k个近邻,根据误差平方和最小的原则,求出k个近邻相应的权值,用k个近邻及相应的权值重构出缺失的数据点。将该算法应用在不同缺失率下的两种化工过程数据中并与望最大化主成分分析(EM-PCA)法和平均值(MA)两种传统的数据恢复算法相比较,该算法的恢复数据误差最小,并且计算速度相比EM-PCA算法平均提高了2倍。实验结果表明,局部加权重构的化工过程数据恢复算法可以有效地对数据进行恢复,提高了数据的利用率,适用于非线性化工过程缺失数据的恢复。展开更多
基金financially supported by National 863 Program (Grants No.2006AA 09A 102-09)National Science and Technology of Major Projects ( Grants No.2008ZX0 5025-001-001)
文摘Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets （POCS） based image restoration method into the seismic data reconstruction field to interpolate irregularly missing traces. For entire dead traces, we transfer the POCS iteration reconstruction process from the time to frequency domain to save computational cost because forward and reverse Fourier time transforms are not needed. In each iteration, the selection threshold parameter is important for reconstruction efficiency. In this paper, we designed two types of threshold models to reconstruct irregularly missing seismic data. The experimental results show that an exponential threshold can greatly reduce iterations and improve reconstruction efficiency compared to a linear threshold for the same reconstruction result. We also analyze the anti- noise and anti-alias ability of the POCS reconstruction method. Finally, theoretical model tests and real data examples indicate that the proposed method is efficient and applicable.
基金supported by Ten Thousand Talent Program of Yunnan Province(Grant No.YNWR-QNBJ-2018-174)the Key Basic Research Program of Yunnan Province,China(Grant No.202101BC070003)+3 种基金National Natural Science Foundation of China(Grant No.31901237)Conservation Program for Plant Species with Extremely Small Populations in Yunnan Province(Grant No.2022SJ07X-03)Key Technologies Research for the Germplasmof Important Woody Flowers in Yunnan Province(Grant No.202302AE090018)Natural Science Foundation of Guizhou Province(Grant No.Qiankehejichu-ZK2021yiban 089&Qiankehejichu-ZK2023yiban 035)。
文摘Rhododendron is famous for its high ornamental value.However,the genus is taxonomically difficult and the relationships within Rhododendron remain unresolved.In addition,the origin of key morphological characters with high horticulture value need to be explored.Both problems largely hinder utilization of germplasm resources.Most studies attempted to disentangle the phylogeny of Rhododendron,but only used a few genomic markers and lacked large-scale sampling,resulting in low clade support and contradictory phylogenetic signals.Here,we used restriction-site associated DNA sequencing(RAD-seq)data and morphological traits for 144 species of Rhododendron,representing all subgenera and most sections and subsections of this species-rich genus,to decipher its intricate evolutionary history and reconstruct ancestral state.Our results revealed high resolutions at subgenera and section levels of Rhododendron based on RAD-seq data.Both optimal phylogenetic tree and split tree recovered five lineages among Rhododendron.Subg.Therorhodion(cladeⅠ)formed the basal lineage.Subg.Tsutsusi and Azaleastrum formed cladeⅡand had sister relationships.CladeⅢincluded all scaly rhododendron species.Subg.Pentanthera(cladeⅣ)formed a sister group to Subg.Hymenanthes(cladeⅤ).The results of ancestral state reconstruction showed that Rhododendron ancestor was a deciduous woody plant with terminal inflorescence,ten stamens,leaf blade without scales and broadly funnelform corolla with pink or purple color.This study shows significant distinguishability to resolve the evolutionary history of Rhododendron based on high clade support of phylogenetic tree constructed by RAD-seq data.It also provides an example to resolve discordant signals in phylogenetic trees and demonstrates the application feasibility of RAD-seq with large amounts of missing data in deciphering intricate evolutionary relationships.Additionally,the reconstructed ancestral state of six important characters provides insights into the innovation of key characters in Rhododendron.
文摘Precipitation is the most discontinuous atmospheric parameter because of its temporal and spatial variability. Precipitation observations at automatic weather stations（AWSs） show different patterns over different time periods. This paper aims to reconstruct missing data by finding the time periods when precipitation patterns are similar, with a method called the intermittent sliding window period（ISWP） technique—a novel approach to reconstructing the majority of non-continuous missing real-time precipitation data. The ISWP technique is applied to a 1-yr precipitation dataset（January 2015 to January 2016）, with a temporal resolution of 1 h, collected at 11 AWSs run by the Indian Meteorological Department in the capital region of Delhi. The acquired dataset has missing precipitation data amounting to 13.66%, of which 90.6% are reconstructed successfully. Furthermore, some traditional estimation algorithms are applied to the reconstructed dataset to estimate the remaining missing values on an hourly basis. The results show that the interpolation of the reconstructed dataset using the ISWP technique exhibits high quality compared with interpolation of the raw dataset. By adopting the ISWP technique, the root-mean-square errors（RMSEs）in the estimation of missing rainfall data—based on the arithmetic mean, multiple linear regression, linear regression,and moving average methods—are reduced by 4.2%, 55.47%, 19.44%, and 9.64%, respectively. However, adopting the ISWP technique with the inverse distance weighted method increases the RMSE by 0.07%, due to the fact that the reconstructed data add a more diverse relation to its neighboring AWSs.
文摘受到外业采集条件限制和施工环境的影响,通常很难采集到理想且完整的规则采样地质雷达数据。地质雷达数据的缺失和不规则采样容易对数据处理过程产生严重干扰,影响后续解释工作。本文给出了一种基于无展开随机QR分解(Uncoiled Randomized QR decomposition,URQR)的地质雷达数据重建方法。首先引入随机QR分解算法实现对地质雷达数据矩阵的降秩计算,并通过利用无展开求平均快速算法,来解决降秩后的Toeplitz矩阵对角线求平均效率低,内存占用量大的问题。然后基于凸集投影理论,实现了无展开随机QR分解算法的数据重建流程。最后,利用本文方法与随机奇异值分解(Randomized Singular Value Decomposition,RSVD)算法,对理论与实际地质雷达缺失道数据进行重建,通过对比质量因子Q值,说明了本文方法重建效果优于RSVD方法,对于大型地质雷达数据的重建,本文方法计算效率明显高于RSVD方法,验证了本文方法的有效性、可行性、效率高的特点。
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。
文摘针对化工过程数据中存在缺失数据的问题,在保持局部数据结构特征的基础上提出了基于局部加权重构的化工过程数据恢复算法。通过定位缺失的数据点并以符号Na N(Not a Number)标记,将缺失的数据集分为完备数据集和不完备数据集。不完备的数据集按照完整性的大小依次找到它们在完备数据集中相应的k个近邻,根据误差平方和最小的原则,求出k个近邻相应的权值,用k个近邻及相应的权值重构出缺失的数据点。将该算法应用在不同缺失率下的两种化工过程数据中并与望最大化主成分分析(EM-PCA)法和平均值(MA)两种传统的数据恢复算法相比较,该算法的恢复数据误差最小,并且计算速度相比EM-PCA算法平均提高了2倍。实验结果表明,局部加权重构的化工过程数据恢复算法可以有效地对数据进行恢复,提高了数据的利用率,适用于非线性化工过程缺失数据的恢复。
