The I ingwu fault is in the eastern boundary of the southern section of Yinchuan graben. It hasa close relation to seismicity in the Lingwu-Wuzhong region.Few researches have been done.In this Paper,on the basis of te...The I ingwu fault is in the eastern boundary of the southern section of Yinchuan graben. It hasa close relation to seismicity in the Lingwu-Wuzhong region.Few researches have been done.In this Paper,on the basis of tee data obtained from field investigation,the activity features inLate Quaternary have been discussed.The vertical displacement and its slip rate have been alsoestimated.The fault is 48km in length,being divided into 3 segments according to geologicaland topographical characteristics.The last rupture along its northern and middle segments wasoccurred in late of Late Pleistocene or early Holocene while that along the southern segmentwas occurred in midle Holocene.The vertical slip rate is estimated as 0.23～025mm/a sinceabout 66ka B.P.based on the vertical displacements of terracesⅠ,Ⅱ and Ⅲ and their ages.展开更多
Based on the fitting on paleoearthquake data of intra-plate regions in the northern part of China and giving a statistical model of time interdependence, the potential damage earthquakes in a definite future period an...Based on the fitting on paleoearthquake data of intra-plate regions in the northern part of China and giving a statistical model of time interdependence, the potential damage earthquakes in a definite future period and characteristics of present shocks along the Lingwu fault have been analyzed by using dangerous probability function and some new data concerned. We have inferred that the fault has entered a period that earthquakes will probably occur. There exists a potential danger that a strong earthquake with M\-S7.0～7.5 will occur in 10～100a.展开更多
利用近红外高光谱成像技术(NIR-HSI),将采集的光谱信息融合图像纹理信息建立分类模型,实现灵武长枣瘀伤等级的判别。采用瘀伤装置获得瘀伤等级为Ⅰ、Ⅱ、Ⅲ、Ⅳ、Ⅴ级的200个长枣样品,并按3∶1的比例划分校正集和预测集。采集不同瘀伤...利用近红外高光谱成像技术(NIR-HSI),将采集的光谱信息融合图像纹理信息建立分类模型,实现灵武长枣瘀伤等级的判别。采用瘀伤装置获得瘀伤等级为Ⅰ、Ⅱ、Ⅲ、Ⅳ、Ⅴ级的200个长枣样品,并按3∶1的比例划分校正集和预测集。采集不同瘀伤等级长枣的近红外高光谱图像,使用ENVI软件提取感兴趣区域(region of interest,ROI)并计算平均光谱值。为消除无用信息的干扰,采用正交信号修正(OSC)、基线校准(Baseline)、多元散射校正(MSC)、移动平均(MA)、卷积平滑(S-G)和去趋势(De-trending)对原始光谱进行预处理并建立偏最小二乘判别分析(PLS-DA)模型;基于最优预处理方法所得的全波段数据采用变量组合集群分析法(VCPA)、无信息消除变量算法(UVE)、竞争性自适应加权抽样算法(CARS)、区间变量迭代空间收缩法(iVISSA)和连续投影算法(SPA)提取特征波长后建立PLS-DA模型;将高光谱图像进行掩膜,利用主成分分析(PCA)获取贡献率最高的主成分图像,并在该图像上采用灰度共生矩阵(GLCM)提取纹理参数,包括能量(ASM)、熵(ENT)、对比度(CON)和相关性(COR),建立图谱融合的PLS-DA模型。结果表明,原始光谱数据建立的PLS-DA模型,校正集和验证集准确率分别为89%和86%;原始光谱经De-trending预处理后的PLS-DA模型效果最优,校正集和预测集准确率均为90%,较原始光谱模型分别提高了1%和4%;基于SPA选择特征波长后建立的PLS-DA模型的校正集和预测集准确率均为90%;De-trending-SPA-COR-PLS-DA图谱融合模型效果最优,模型校正集和预测集准确率均为92%。因此,利用近红外高光谱成像技术融合纹理信息可实现不同瘀伤等级灵武长枣的快速无损判别。展开更多
基金This project was sponsored by the Joint Earthquake Seience Foundation (197013) and the Commission of Science and Technology, Ningxia Hui Autonomous Region, China.
文摘The I ingwu fault is in the eastern boundary of the southern section of Yinchuan graben. It hasa close relation to seismicity in the Lingwu-Wuzhong region.Few researches have been done.In this Paper,on the basis of tee data obtained from field investigation,the activity features inLate Quaternary have been discussed.The vertical displacement and its slip rate have been alsoestimated.The fault is 48km in length,being divided into 3 segments according to geologicaland topographical characteristics.The last rupture along its northern and middle segments wasoccurred in late of Late Pleistocene or early Holocene while that along the southern segmentwas occurred in midle Holocene.The vertical slip rate is estimated as 0.23～025mm/a sinceabout 66ka B.P.based on the vertical displacements of terracesⅠ,Ⅱ and Ⅲ and their ages.
文摘Based on the fitting on paleoearthquake data of intra-plate regions in the northern part of China and giving a statistical model of time interdependence, the potential damage earthquakes in a definite future period and characteristics of present shocks along the Lingwu fault have been analyzed by using dangerous probability function and some new data concerned. We have inferred that the fault has entered a period that earthquakes will probably occur. There exists a potential danger that a strong earthquake with M\-S7.0～7.5 will occur in 10～100a.
文摘利用近红外高光谱成像技术(NIR-HSI),将采集的光谱信息融合图像纹理信息建立分类模型,实现灵武长枣瘀伤等级的判别。采用瘀伤装置获得瘀伤等级为Ⅰ、Ⅱ、Ⅲ、Ⅳ、Ⅴ级的200个长枣样品,并按3∶1的比例划分校正集和预测集。采集不同瘀伤等级长枣的近红外高光谱图像,使用ENVI软件提取感兴趣区域(region of interest,ROI)并计算平均光谱值。为消除无用信息的干扰,采用正交信号修正(OSC)、基线校准(Baseline)、多元散射校正(MSC)、移动平均(MA)、卷积平滑(S-G)和去趋势(De-trending)对原始光谱进行预处理并建立偏最小二乘判别分析(PLS-DA)模型;基于最优预处理方法所得的全波段数据采用变量组合集群分析法(VCPA)、无信息消除变量算法(UVE)、竞争性自适应加权抽样算法(CARS)、区间变量迭代空间收缩法(iVISSA)和连续投影算法(SPA)提取特征波长后建立PLS-DA模型;将高光谱图像进行掩膜,利用主成分分析(PCA)获取贡献率最高的主成分图像,并在该图像上采用灰度共生矩阵(GLCM)提取纹理参数,包括能量(ASM)、熵(ENT)、对比度(CON)和相关性(COR),建立图谱融合的PLS-DA模型。结果表明,原始光谱数据建立的PLS-DA模型,校正集和验证集准确率分别为89%和86%;原始光谱经De-trending预处理后的PLS-DA模型效果最优,校正集和预测集准确率均为90%,较原始光谱模型分别提高了1%和4%;基于SPA选择特征波长后建立的PLS-DA模型的校正集和预测集准确率均为90%;De-trending-SPA-COR-PLS-DA图谱融合模型效果最优,模型校正集和预测集准确率均为92%。因此,利用近红外高光谱成像技术融合纹理信息可实现不同瘀伤等级灵武长枣的快速无损判别。
