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图的边覆盖染色与分数边覆盖染色 被引量:6
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作者 王纪辉 刘桂真 《山东大学学报(理学版)》 CAS CSCD 北大核心 2005年第3期1-4,共4页
讨论了图G=(V,E)的分数边覆盖色数χ′cf(G)的概念和性质,给出计算χ′cf(G)的一个精确公式,即χ′cf(G)=minS2·|C[S]||S|+1,其中S为V(G)的非空子集且|S|为奇数,C[S]是E(G)的至少有一个端点在S中的边构成的子集,并证明δ-1<χ′... 讨论了图G=(V,E)的分数边覆盖色数χ′cf(G)的概念和性质,给出计算χ′cf(G)的一个精确公式,即χ′cf(G)=minS2·|C[S]||S|+1,其中S为V(G)的非空子集且|S|为奇数,C[S]是E(G)的至少有一个端点在S中的边构成的子集,并证明δ-1<χ′cf(G)δ;同时讨论了χ′cf(G)与图G的边覆盖色数χ′c(G)的关系,并利用χ′cf(G)与χ′c(G)的关系对图进行分类. 展开更多
关键词 覆盖染色 分数覆盖染色 色数
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分数覆盖图
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作者 周思中 邱云明 《华东船舶工业学院学报》 北大核心 2005年第4期37-40,共4页
设G是一个图,并设h是定义在图G的边集E(G)上的一个函数,使对任意的e∈E(G)有h(e)∈[0,1]。令dhG(x)=∑e xh(e),则称dhG(x)是G中顶点x的分数度。若h满足对任意的x∈V(G)有g(x)≤dhG(x)≤f(x),则称h是G的一个分数(g,f)-因子。如果对图G中... 设G是一个图,并设h是定义在图G的边集E(G)上的一个函数,使对任意的e∈E(G)有h(e)∈[0,1]。令dhG(x)=∑e xh(e),则称dhG(x)是G中顶点x的分数度。若h满足对任意的x∈V(G)有g(x)≤dhG(x)≤f(x),则称h是G的一个分数(g,f)-因子。如果对图G中的任何两条边e1和e2,G都有一个分数(g,f)-因子h满足h(e1)=1和h(e2)=1,则称图G为分数(g,f)-2-覆盖图。本文给出了一个图是分数(g,f)-2-覆盖图的充分必要条件。 展开更多
关键词 分数(G F)-因子 分数(g f)2-覆盖
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关于分数(g,f)-2-覆盖图
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作者 周思中 薛秀谦 《安徽大学学报(自然科学版)》 CAS 2004年第2期22-27,共6页
设G是一个图,并设h是定义在图G的边集E(G)上的一个函数,使对任意的e∈E(G),有h(e)∈[0,1]。令dhG(x)= x瘕?h(e),则称dhG(x)是G中顶点x的分数度。若h满足对任意的x∈V(G),有g(x)≤dhG(x)≤f(x),则称h是G的一个分数(g,f)-因子。一个图称... 设G是一个图,并设h是定义在图G的边集E(G)上的一个函数,使对任意的e∈E(G),有h(e)∈[0,1]。令dhG(x)= x瘕?h(e),则称dhG(x)是G中顶点x的分数度。若h满足对任意的x∈V(G),有g(x)≤dhG(x)≤f(x),则称h是G的一个分数(g,f)-因子。一个图称为分数(g,f)-2-覆盖图,如果对图G中的任何两条边e1和e2,G都有一个分数(g,f)-因子h满足h(e1)=1和h(e2)。本文给出了一个图是分数(g,f) 2 覆盖图的充分必要条件。 展开更多
关键词 分数(G F)-因子 分数(g f)-2-覆盖
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分数(g,f)-2-覆盖图和分数(g,f)-2-消去图 被引量:1
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作者 周思中 《广西科学》 CAS 2004年第3期177-178,182,共3页
分别给出分数 (g,f ) - 2 -覆盖图和分数 (g,f ) - 2 -消去图的概念 ,以及一个图是分数 (g,f ) - 2 -覆盖图和分数 (g,f ) - 2 -消去图的若干充分条件 .
关键词 分数(g f)-2-覆盖 分数(g f)-2-消去图 分数(G F)-因子
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分数(g,f)-因子、分数(g,f)-覆盖图和分数(g,f)-消去图
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作者 周思中 《甘肃科学学报》 2004年第4期8-10,共3页
 给出了一个图有分数(g,f)-因子的两个充分条件,并给出了一个图是分数(g,f)-覆盖图和分数(g,f)-消去图的两个充分必要条件.
关键词 分数(G F)-因子 分数(g f)-覆盖 分数(g f)-消去图
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图中具有分数(g,f)-因子的若干充分条件 被引量:1
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作者 周思中 尚长明 《工程数学学报》 CSCD 北大核心 2007年第2期329-333,共5页
设g和f分别是定义在图G的顶点集合V(G)上的整数值函数且对每个x∈V(G)有0≤g(x)≤f(x)。本文给出了一个图有分数(g,f)-因子的若干充分条件。
关键词 分数因子 分数覆盖 分数消去图
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基于差分隐私的频繁项集挖掘的启发式算法 被引量:4
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作者 陈婷婷 龙士工 《计算机工程与设计》 北大核心 2019年第2期412-417,共6页
针对频繁项目集挖掘结果直接发布可能会造成严重的个人隐私泄露,提出一种满足差分隐私的频繁项目集挖掘算法。为降低差分隐私的全局敏感度,根据候选项的覆盖分数和项集与事务距离两个指标,采用启发式截断算法进行事务截断,尽可能多地使... 针对频繁项目集挖掘结果直接发布可能会造成严重的个人隐私泄露,提出一种满足差分隐私的频繁项目集挖掘算法。为降低差分隐私的全局敏感度,根据候选项的覆盖分数和项集与事务距离两个指标,采用启发式截断算法进行事务截断,尽可能多地使截断后的事务保留原事务的频繁项信息。采用最大支持度估计策略生成候选项集,降低因事务截断和剪枝操作带来的误差。实验结果对比分析表明,提出算法满足差分隐私保护,挖掘的频繁项集具有较好的效用。 展开更多
关键词 差分隐私 频繁项目集 启发式截断 覆盖分数 项集与事务距离 最大支持度估计策略
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Effects of RapidEye Imagery's Red-edge Band and Vegetation Indices on Land Cover Classification in an Arid Region 被引量:9
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作者 LI Xianju CHEN Gang +3 位作者 LIU Jingyi CHEN Weitao CHENG Xinwen LIAO Yiwei 《Chinese Geographical Science》 SCIE CSCD 2017年第5期827-835,共9页
Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was eff... Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidE ye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement(3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions. 展开更多
关键词 arid region land cover classification RapidEye red-edge band vegetation indices random forest Dunhuang Basin
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Land Cover Classification with Multi-source Data Using Evidential Reasoning Approach 被引量:3
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作者 LI Huapeng ZHANG Shuqing +1 位作者 SUN Yan GAO Jing 《Chinese Geographical Science》 SCIE CSCD 2011年第3期312-321,共10页
Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application ... Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application of multi-source data becomes necessary.This paper presents an evidential reasoning (ER) approach to incorporate Landsat TM imagery,altitude and slope data.Results show that multi-source data contribute to the classification accuracy achieved by the ER method,whereas play a negative role to that derived by maximum likelihood classifier (MLC).In comparison to the results derived based on TM imagery alone,the overall accuracy rate of the ER method increases by 7.66% and that of the MLC method decreases by 8.35% when all data sources (TM plus altitude and slope) are accessible.The ER method is regarded as a better approach for multi-source image classification.In addition,the method produces not only an accurate classification result,but also the uncertainty which presents the inherent difficulty in classification decisions.The uncertainty associated to the ER classification image is evaluated and proved to be useful for improved classification accuracy. 展开更多
关键词 evidential reasoning Dempster-Shafer theory of evidence multi-source data geographic ancillary data land cover classification classification uncertainty
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Integrating TM and Ancillary Geographical Data with Classification Trees for Land Cover Classification of Marsh Area 被引量:14
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作者 NA Xiaodong ZHANG Shuqing +3 位作者 ZHANG Huaiqing LI Xiaofeng YU Huan LIU Chunyue 《Chinese Geographical Science》 SCIE CSCD 2009年第2期177-185,共9页
The main objective of this research is to determine the capacity of land cover classification combining spec- tral and textural features of Landsat TM imagery with ancillary geographical data in wetlands of the Sanjia... The main objective of this research is to determine the capacity of land cover classification combining spec- tral and textural features of Landsat TM imagery with ancillary geographical data in wetlands of the Sanjiang Plain, Heilongjiang Province, China. Semi-variograms and Z-test value were calculated to assess the separability of grey-level co-occurrence texture measures to maximize the difference between land cover types. The degree of spatial autocorrelation showed that window sizes of 3×3 pixels and 11×11 pixels were most appropriate for Landsat TM im- age texture calculations. The texture analysis showed that co-occurrence entropy, dissimilarity, and variance texture measures, derived from the Landsat TM spectrum bands and vegetation indices provided the most significant statistical differentiation between land cover types. Subsequently, a Classification and Regression Tree (CART) algorithm was applied to three different combinations of predictors: 1) TM imagery alone (TM-only); 2) TM imagery plus image texture (TM+TXT model); and 3) all predictors including TM imagery, image texture and additional ancillary GIS in- formation (TM+TXT+GIS model). Compared with traditional Maximum Likelihood Classification (MLC) supervised classification, three classification trees predictive models reduced the overall error rate significantly. Image texture measures and ancillary geographical variables depressed the speckle noise effectively and reduced classification error rate of marsh obviously. For classification trees model making use of all available predictors, omission error rate was 12.90% and commission error rate was 10.99% for marsh. The developed method is portable, relatively easy to im- plement and should be applicable in other settings and over larger extents. 展开更多
关键词 land cover classification classification trees Landsat TM ancillary geographical data MARSH
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分数(g,f,m)-覆盖图的充要条件
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作者 刘树利 刘素洁 《数学的实践与认识》 CSCD 北大核心 2013年第13期217-220,共4页
G是一个图,g和f是两个定义在V(G)上的非负整数值函数,并且对任意的x∈V(G),满足g(x)≤f(x).称图G是分数(g,f,m)-覆盖图,如果存在图G的分数(g,f)-因子G[F_h]满足对任意的e∈E(H)有h(e)=1,其中H是图G的m条边的子图.证明了一个图是分数(g,f... G是一个图,g和f是两个定义在V(G)上的非负整数值函数,并且对任意的x∈V(G),满足g(x)≤f(x).称图G是分数(g,f,m)-覆盖图,如果存在图G的分数(g,f)-因子G[F_h]满足对任意的e∈E(H)有h(e)=1,其中H是图G的m条边的子图.证明了一个图是分数(g,f,m)-覆盖图的充要条件,并得到了几个推论. 展开更多
关键词 分数(G F)-因子 分数(g f m)-覆盖
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Geospatial knowledge-based verification and improvement of GlobeLand30 被引量:4
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作者 ZHANG WeiWei CHEN Jun +6 位作者 LIAO AnPing HAN Gang CHEN XueHong CHEN LiJun PENG Shu WU Hao ZHANG Jun 《Science China Earth Sciences》 SCIE EI CAS CSCD 2016年第9期1709-1719,共11页
Assuring the quality of land-cover data is one of the major challenges for large- area mapping projects. Although the use of geospatial knowledge and ancillary data in improving land-cover classification has been stud... Assuring the quality of land-cover data is one of the major challenges for large- area mapping projects. Although the use of geospatial knowledge and ancillary data in improving land-cover classification has been studied since the early 1980 s, mature methods and efficient supporting tools are still lacking. This paper presents a geospatial knowledge-based verification and improvement approach for global land cover(GLC) mapping at 30-m resolution. A set of verification rules is derived from three types of land cover and its change knowledge(natural, cultural and temporal constraints). A group of web-based supporting tools is developed to facilitate the integration of and access to large amounts of ancillary data and to support online data manipulation and analysis as well as collaborative verification workflows. With this approach, two 30-m GLC datasets(Globe Land-2000 and Globe Land-2010) were verified and modified. The results indicate that the data quality of Globe Land30 has been largely improved. 展开更多
关键词 Land cover Data quality Geospatial knowledge VERIFICATION CONSISTENCY GlobeLand30
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A multi-resolution global land cover dataset through multisource data aggregation 被引量:24
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作者 YU Le WANG Jie +3 位作者 LI XueCao LI CongCong ZHAO YuanYuan GONG Peng 《Science China Earth Sciences》 SCIE EI CAS 2014年第10期2317-2329,共13页
Recent developments of 30 m global land characterization datasets (e.g., land cover, vegetation continues field) represent the finest spatial resolution inputs for global scale studies. Here, we present results from... Recent developments of 30 m global land characterization datasets (e.g., land cover, vegetation continues field) represent the finest spatial resolution inputs for global scale studies. Here, we present results from further improvement to land cover map- ping and impact analysis of spatial resolution on area estimation for different land cover types. We proposed a set of methods to aggregate two existing 30 m resolution circa 2010 global land cover maps, namely FROM-GLC (Finer Resolution Observa- tion and Monitoring-Global Land Cover) and FROM-GLC-seg (Segmentation), with two coarser resolution global maps on development, i.e., Nighttime Light Impervious Surface Area (NL-ISA) and MODIS urban extent (MODIS-urban), to produce an improved 30 m global land cover map-FROM-GLC-agg (Aggregation). It was pos-processed using additional coarse res- olution datasets (i.e., MCD12Q1, GlobCover2009, MOD44W etc.) to reduce land cover type confusion. Around 98.9% pixels remain 30 m resolution after some post-processing to this dataset. Based on this map, majority aggregation and proportion ag- gregation approaches were employed to create a multi-resolution hierarchy (i.e., 250 m, 500 m, 1 km, 5 km, 10 km, 25 km, 50 km, 100 km) of land cover maps to meet requirements for different resolutions from different applications. Through accuracy assessment, we found that the best overall accuracies for the post-processed base map (at 30 m) and the three maps subse- quently aggregated at 250 m, 500 m, 1 km resolutions are 69.50%, 76.65%, 74.65%, and 73.47%, respectively. Our analysis of area-estimation biases for different land cover types at different resolutions suggests that maps at coarser than 5 km resolution contain at least 5% area estimation error for most land cover types. Proportion layers, which contain precise information on land cover percentage, are suggested for use when coarser resolution land cover data are required. 展开更多
关键词 spatial aggregation LANDSAT MODIS BIODIVERSITY climate change MULTI-RESOLUTION majority vote
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The first all-season sample set for mapping global land cover with Landsat-8 data 被引量:25
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作者 Congcong Li Peng Gong +18 位作者 Jie Wang Zhiliang Zhu Gregory S. Biging Cui Yuan Tengyun Hu Haiying Zhang Qi Wang Xuecao Li Xiaoxuan Liu Yidi Xu Jing Guo Caixia Liu Kwame O. Hackman Meinan Zhang Yuqi Cheng Le Yu Jun Yang Huabing Huang Nicholas Clinton 《Science Bulletin》 SCIE EI CAS CSCD 2017年第7期508-515,共8页
We report the world's first all-season training and validation sample sets for global land cover classification with Landsat-8 data.Prior to this,such samples were only available at a single date primarily from th... We report the world's first all-season training and validation sample sets for global land cover classification with Landsat-8 data.Prior to this,such samples were only available at a single date primarily from the growing season.It is unknown how much limitation such a single-date sample has to mapping global land cover in other seasons of the year.To answer this question,we selected available Landsat-8 images from four seasons and collected training and validation samples from them.We compared the performances of training samples in different seasons using Random Forest algorithm.We found that the use of training samples from any individual season would result in the best overall classification accuracy when validated by samples in the same season.The global overall accuracy from combined best seasonal results was 67.2% when classifying the 11 Level-1 classes in the Finer Resolution Observation and Monitoring of Global Land Cover(FROM-GLC) classification system.The use of training samples from all seasons(named all-season training sample set hereafter) produced an overall accuracy of 67.0%.We also tested classification within 10° latitude 60° longitude zones using all-season training subsample within each zone and obtained an overall accuracy of 70.2%.This indicates that properly grouped subsamples in space can help improve classification accuracies.All the results in this study seem to suggest that it is possible to use an all-season training sample set to reach global optimality with universal applicability in classifying images acquired at any time of a year for global land cover mapping. 展开更多
关键词 Training sample VALIDATION Latitudinal zones Anytime ANYWHERE
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Effects of Vegetation Cover and Rainfall Intensity on Sediment-Bound Nutrient Loss,Size Composition and Volume Fractal Dimension of Sediment Particles 被引量:27
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作者 ZHANG Guan-Hua LIU Guo-Bin +1 位作者 WANG Guo-Liang WANG Yu-Xia 《Pedosphere》 SCIE CAS CSCD 2011年第5期676-684,共9页
Vegetation and rainfall are two important factors affecting soil erosion and thus resulting in nutrient loss in the Chinese Loess Plateau.A field experiment was conducted to investigate the effects of rainfall intensi... Vegetation and rainfall are two important factors affecting soil erosion and thus resulting in nutrient loss in the Chinese Loess Plateau.A field experiment was conducted to investigate the effects of rainfall intensities(60,100 and 140 mm h-1) and vegetation(Caragana korshinskii) coverages(0%,30% and 80%) on soil loss,nutrient loss,and the composition and volume fractal dimension of eroded sediment particles under simulated rainfall conditions.The results showed that vegetation cover,rainfall intensity and their interaction all had significant effects on sediment transport and the sedimentbound nutrient loss.Higher rainfall intensity and lower coverage led to higher sediment and nutrient losses.Positive linear relationships were observed between soil loss and nutrient loss.The treatments showed more significant effects on the enrichment ratio(ER) of nitrogen(ERN) than organic matter(EROM) and phosphorus(ERP).Compared with the original surface soil,the eroded sediment contained more fine particles.Under the same coverage,the clay content significantly decreased with increasing rainfall intensity.The ER of sediment-bound nutrients was positively correlated with that of clay,suggesting that the clay fraction was preferentially eroded and soil nutrients were mainly adsorbed onto or contained within this fraction.There were increments in the fractal dimension of the sediment particles compared to that of the original surface soil.Moreover,the fractal dimension was positively correlated with clay,silt,and sediment-bound OM,N,and P contents,whereas it was negatively correlated with sand content.This study demonstrated that fractal dimension analysis can be used to characterize differences in particle-size distribution and nutrient loss associated with soil erosion. 展开更多
关键词 fractal features Loess Plateau particle-size distribution runoff nutrients simulated rainfall
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AntarcticaLC2000:The new Antarctic land cover database for the year 2000 被引量:5
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作者 HUI FengMing KANG Jing +6 位作者 LIU Yan CHENG Xiao GONG Peng WANG Fang LI Zhan YE YuFang GUO ZiQi 《Science China Earth Sciences》 SCIE EI CAS CSCD 2017年第4期686-696,共11页
Antarctica plays a key role in global energy balance and sea level change.It has been conventionally viewed as a whole ice body with high albedo in General Circulation Models or Regional Climate Models and the differe... Antarctica plays a key role in global energy balance and sea level change.It has been conventionally viewed as a whole ice body with high albedo in General Circulation Models or Regional Climate Models and the differences of land cover has usually been overlooked.Land cover in Antarctica is one of the most important drivers of changes in the Earth system.Detailed land cover information over the Antarctic region is necessary as spatial resolution improves in land process models.However,there is a lack of complete Antarctic land cover dataset derived from a consistent data source.To fill this data gap,we have produced a database named Antarctic Land Cover Database for the Year 2000(AntarcticaLC2000) using Landsat Enhanced Thematic Mapper Plus(ETM+) data acquired around 2000 and Moderate Resolution Imaging Spectrometer(MODIS) images acquired in the austral summer of 2003/2004 according to the criteria for the 1:100000-scale.Three land cover types were included in this map,separately,ice-free rocks,blue ice,and snow/firn.This classification legend was determined based on a review of the land cover systems in Antarctica(LCCSA) and an analysis of different land surface types and the potential of satellite data.Image classification was conducted through a combined usage of computer-aided and manual interpretation methods.A total of 4067 validation sample units were collected through visual interpretation in a stratified random sampling manner.An overall accuracy of 92.3%and the Kappa coefficient of 0.836 were achieved.Results show that the areas and percentages of ice-free rocks,blue ice,and snow/firn are 73268.81 km2(0.537%),225937.26 km2(1.656%),and 13345460.41 km2(97.807%),respectively.The comparisons with other different data proved a higher accuracy of our product and a more advantageous data quality.These indicate that AntarcticaLC2000,the new land cover dataset for Antarctica entirely derived from satellite data,is a reliable product for a broad spectrum of applications. 展开更多
关键词 Snowdrift process Air-snow interaction Ice core dating Ultrasonic sounder Post depositional process
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