共查询到19条相似文献，搜索用时 187 毫秒
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关于丛书分类和著录方法的探讨 总被引：4，自引：3，他引：1
张立新 《农业图书情报学刊》2005,17(7):159-161
本文通过对丛书的分类方法和著录方法的探讨及实例的分析,指出丛书集中分类和分散分类、分散著录和多层次著录的具体方式,并分析了丛书与多卷书的区别和联系,表明多卷书集中分类,分卷,分散著录的观点。 相似文献
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李祝华 《云南农业大学学报(自然科学版)》2009,3(3):117-120
从书次号的定义和丛书的特点出发,对丛书的著录类型进行分析;采用不同的著录形式和著录方法对不同类型的丛书进行探讨,旨在对比、分析分散著录、集中分类和分散分类的优缺点,更好地指导丛书的著录工作。 相似文献
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丛书的分类、著录与检索 总被引：2，自引：1，他引：1
结合丛书类型、学科特点、读者阅读心理及检索习惯,提出了丛书分类标引及排架的相关建议。并从读者检索的角度．论述了不同类型丛书的综合（分散）著录原则及同系列丛书著录的规范一致性原则;同时,针对目前丛书出版印刷的无序与混乱,总结出4种丛编题名著录模式。 相似文献
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童敏 《农业图书情报学刊》2005,17(12):187-189
针对目前多卷书和丛书的处理较为混乱的状况,通过对图书著录单元和图书借阅权限的描述,提出以IS-BN作为多卷书和丛书集中或分散处理的依据的观点,即有多少个ISBN就作多少条著录数据,并阐述了集中著录、分散著录、分册著录的区别,采用ISBN作为依据的合理性及其5大好处。 相似文献
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机读目录是计算机在图书馆中应用的产物，它的特点是一次输入可有多种形式的输出，便于读者从不同角度检索图书，大大提高读者检索效率，而在机编过程中，多卷书、丛书的著录工作比较复杂，有一定难度，要做好多卷书、丛书的著录，首先应划清丛书与多卷书的界线…… 相似文献
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夏新阳 《农业图书情报学刊》1987,(4)
为了满足广大农业科技工作者、广大农民学习农业科学技术知识的迫切需要,出版部门近几年来,出版了不少受群众欢迎的农业丛书。我馆做为农业专业图书馆,收集这类农业丛书占新到中文图书的相当大比例。如何处理这类农业丛书?我馆基本上是按国家标准《中文普通图书著录规则》为依据。下面结合我馆具体情况谈谈我们如何处理好农业丛书的著录以及农业丛书著录的具 相似文献
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杨文霞 《农业图书情报学刊》2007,19(7):171-172,175
丛书在CALIS中著录和分编,没有统一划分的原则,没有真正体现丛书的作用和分编的意义。从多年的分编经验中总结出若干分编要目,从丛书的定义,著录规范,注意原则,分编事宜,馆藏分类号的给出等几方面进行了阐述,以供商榷。 相似文献
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孟繁华 《农业图书情报学刊》2015,27(9):73-76
结合工作实践,针对港台版中文图书著录信息源选取及检索点规范著录中出现的一些问题,从题名、责任说明及丛书项等几个方面进行分析,以期为港台版中文图书编目工作的标准化提供有益借鉴。 相似文献
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This paper describes a supervised learning approach to sow-activity classification from accelerometer measurements. In the proposed methodology, pairs of accelerometer measurements and activity types are considered as labeled instances of a usual supervised classification task. Under this scenario sow-activity classification can be approached with standard machine learning methods for pattern classification. Individual predictions for elements of times series of arbitrary length are combined to classify it as a whole. An extensive comparison of representative learning algorithms, including neural networks, support vector machines, and ensemble methods, is presented. Experimental results are reported using a data set for sow-activity classification collected in a real production herd. The data set, which has been widely used in related works, includes measurements from active (Feeding, Rooting, Walking) and passive (Lying Laterally, Lying Sternally) activities. When classifying 1-s length observations, the best method achieved an average recognition rate of 74.64%, for the five activities. When classifying 2-min length time series, the performance of the best model increased to 80%. This is an important improvement from the 64% average recognition rate for the same five activities obtained in previous work. The pattern classification approach was also evaluated in alternative scenarios, including distinguishing between active and passive categories, and a multiclass setting. In general, better results were obtained when using a tree-based logitboost classifier. This method proved to be very robust to noise in observations. Besides its higher performance, the suggested method is more flexible than previous approaches, since time series of any length can be analyzed. 相似文献
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苹果属植物花器形态特征与分类学研究 总被引：1，自引：0，他引：1
文章研究了苹果属（ＭａｌｕｓＭｉｌ）４９个生物型的花器形态解剖学特征，对主要特征进行了主成份和性状相关分析。结果表明，苹果属植物花器形态特征质量性状变异很少，呈显著的数量变异特点，组系间无明显间断。花器各部份的颜色间，各部份被毛与花柱平均数间以及花丝、花柱和花瓣数等性状与萼片外被毛之间呈明显正相关。各主成份的贡献率分散，累计贡献率增长缓慢，说明苹果属植物花器形态变异的多方向性。文章还讨论了花器特征的分类意义及一些种间的亲缘关系。 相似文献
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湘东板页岩发育水耕人为土的土系分类初探 总被引：1，自引：0，他引：1
选取湘东地区6个板页岩发育的典型水耕人为土剖面,通过调查当地成土环境,描述土壤剖面形态和室内分析理化性质,按中国土壤系统分类方案,探索类似母质/母土条件下水耕人为土的基层分类指标和建立土系。在水耕人为土亚纲下,划分出铁聚和简育水耕人为土2个土类,普通铁聚水耕人为土和普通简育水耕人为土2个亚类,进一步划分出4个土族和6个土系(五峰系、黄田系、洪鸟系、拗才系、晋坪系和城望系)。同一地区类似母质发育的水耕人为土,系统分类的定量化指标(颗粒大小级别和质地层次差异)比发生分类的定性判定具有更强的划分能力,能更有效的反映基层土壤类型的生产性能,对当地农作物生产和土壤改良更具有指导意义。 相似文献
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Early detection and classification of plant diseases with Support Vector Machines based on hyperspectral reflectance 总被引：5，自引：0，他引：5
T. Rumpf A.-K. Mahlein U. Steiner H.-W. Dehne 《Computers and Electronics in Agriculture》2010,74(1):91-162
Automatic methods for an early detection of plant diseases are vital for precision crop protection. The main contribution of this paper is a procedure for the early detection and differentiation of sugar beet diseases based on Support Vector Machines and spectral vegetation indices. The aim was (I) to discriminate diseased from non-diseased sugar beet leaves, (II) to differentiate between the diseases Cercospora leaf spot, leaf rust and powdery mildew, and (III) to identify diseases even before specific symptoms became visible. Hyperspectral data were recorded from healthy leaves and leaves inoculated with the pathogens Cercospora beticola, Uromyces betae or Erysiphe betae causing Cercospora leaf spot, sugar beet rust and powdery mildew, respectively for a period of 21 days after inoculation. Nine spectral vegetation indices, related to physiological parameters were used as features for an automatic classification. Early differentiation between healthy and inoculated plants as well as among specific diseases can be achieved by a Support Vector Machine with a radial basis function as kernel.The discrimination between healthy sugar beet leaves and diseased leaves resulted in classification accuracies up to 97%. The multiple classification between healthy leaves and leaves with symptoms of the three diseases still achieved an accuracy higher than 86%. Furthermore the potential of presymptomatic detection of the plant diseases was demonstrated. Depending on the type and stage of disease the classification accuracy was between 65% and 90%. 相似文献
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利用显微解剖方法对紫金牛属(Ardisia)14个类群的9个花部形态特征进行解剖学研究。结果表明,紫金牛属植物的花瓣基部腺状乳突、子房毛被、胚珠轮数可作为属下等级划分依据,而花瓣、萼片、子房斑点、胎座形状和胚珠数量可作为种间划分的重要依据。同一类群的胚珠轮数较稳定,而胚珠数量常有变化。补充和细化了花部结构的一些性状,特别是轮叶紫金牛。澄清了郎伞木与朱砂根、大罗伞树的关系。推测了一些花部性状的演化趋势。紫金牛属的花部特征在种间具有较大差异,可作为种间划分的依据,亦可以作为属下等级划分的重要参考,具有重要的分类学意义。 相似文献
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Early-season crop type mapping could provide important information for crop growth monitoring and yield prediction, but the lack of ground-surveyed training samples is the main challenge for crop type identification. Although reference time series based method(RBM) has been proposed to identify crop types without the use of ground-surveyed training samples, the methods are not suitable for study regions with small field size because the reference time series are mainly generated using data set with low spatial resolution. As the combination of Landsat data and Sentinel-2 data could increase the temporal resolution of 30-m image time series, we improved the RBM by generating reference normalized difference vegetation index(NDVI)/enhanced vegetation index(EVI) time series at 30-m resolution(30-m RBM) using both Landsat and Sentinel-2 data, then tried to estimate the potential of the reference NDVI/EVI time series for crop identification at early season. As a test case, we tried to use the 30-m RBM to identify major crop types in Hengshui, China at early season of 2018, the results showed that when the time series of the entire growing season were used for classification, overall classification accuracies of the 30-m RBM were higher than 95%, which were similar to the accuracies acquired using the ground-surveyed training samples. In addition, cotton, spring maize and summer maize distribution could be accurately generated 8, 6 and 8 weeks before their harvest using the 30-m RBM; but winter wheat can only be accurately identified around the harvest time phase. Finally, NDVI outperformed EVI for crop type classification as NDVI had better separability for distinguishing crops at the green-up time phases. Comparing with the previous RBM, advantage of 30-m RBM is that the method could use the samples of the small fields to generate reference time series and process image time series with missing value for early-season crop classification; while, samples collected from multiple years should be further used so that the reference time series could contain more crop growth conditions. 相似文献
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基于Sentinel-2时序多特征的植被分类 总被引：1，自引：0，他引：1
植被分类是研究森林资源状况和动态变化规律的基础,利用遥感手段可以更加快速、准确地识别植被类型。以位于内蒙古赤峰市喀喇沁旗西南部的旺业甸实验林场为研究对象进行植被分类。采用分层分类的思想,首先根据植被物候特征选取植被生长旺盛时期的影像,计算归一化植被指数（normalized difference vegetation index,NDVI）并设定合适的阈值将研究区内的植被提取出来,剩余部分归为非植被。然后选取NDVI时间序列、最佳时相的Sentinel-2数据中10个波段的光谱反射率特征和主成分分析前3个分量的纹理特征作为分类特征,利用支持向量机分类器将研究区内的植被类型分为耕地、草地、常绿针叶林、落叶针叶林和落叶阔叶林五大类,并将分类结果与最大似然法、NDVI时序+光谱特征的分类结果进行对比分析。NDVI时序+光谱特征+纹理特征的多特征植被分类总体精度达87.64%,Kappa系数为0.85,分别比最大似然法和结合NDVI时序+光谱特征的分类总体精度提高了15.73%和14.61%,Kappa系数提高了0.20和0.18。其中常绿针叶林和耕地的分类结果与实地调查情况高度一致,分类精度分别达到95.65%和92.31%。从而得出:①基于多特征的分类方法有助于提高分类精度;②NDVI时序特征对于植被的区分具有很大帮助;③采用分层分类的思想,首先将研究区内的植被提取出来,可以排除非植被因素的干扰,有效提高植被类型的分类精度。 相似文献
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【目的】微波遥感因具有全天时、全天候数据获取的特点,在多云雨的中国南方水稻识别研究中表现出巨大潜力。本研究通过对比Sentinel-1SAR遥感数据和Sentinel-2光学遥感数据用于水稻遥感制图的效果,分析光学和SAR遥感数据对于单双季稻识别结果的一致性,并探索水稻识别的最优SAR影像特征。【方法】本研究使用Sentinel-1/2卫星数据,基于面向对象的随机森林分类算法和Google Earth Engine平台,提取洞庭湖平原4个典型水稻种植区的单双季稻空间分布。通过比较9种不同传感器和特征组合场景的分类精度和分类结果统计指标,并计算NDVI和SAR特征时序（VH、VV、VH/VV）的R2和DTW距离,分析识别单双季稻的最优SAR特征,评估光学和SAR遥感数据对于单双季稻识别结果的一致性。【结果】VH、VV和VH/VV时序识别单双季的总体精度分别为90.42%、82.08%和88.33%,而联合VH和VH/VV时序识别单双季稻的总体精度可达91.67%。VH（VH/VV、VV）时序与单双季稻NDVI时序的R2和DTW距离分别为0.870（0.915、0.986）、4.715（1.896、5.506）（单季稻）和0.597（0.783、0.673）、2.396（1.839、3.441）（双季稻）。较高的R2和较低的DTW距离说明单双季稻的VH/VV时序与NDVI时序相关度更高,可以较好地反映单双季稻的生长周期规律。同时,VH可以较好地反映单双季稻移栽期的淹水特征。基于光学数据和SAR数据在6个时间窗口的特征（S-2：NDVI、EVI、LSWI;S-1：VH、VH/VV）识别单双季稻的总体精度分别为91.25%和90.00%,识别结果面积相关性可达95.70%。【结论】SAR遥感数据与光学遥感数据水稻识别结果一致性较高。应用Sentinel-1在多云雨区识别单双季稻具有巨大潜力,VH和VH/VV后向散射系数时序是识别水稻的优质特征。研究结果为多云多雨区使用SAR数据进行特征优选以高精度识别单双季稻提供了重要技术支撑。 相似文献