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基于雷达信号转换的多维空间声音识别技术
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作者 孟东 《电声技术》 2024年第6期150-152,156,共4页
为增加雷达信号的识别方式,提出一种基于雷达信号转换的多维空间声音识别技术。首先,将脉冲式的雷达信号拼接为连续特征声音信号;其次,使用高斯混合模型(Gaussian Mixed Model,GMM)训练拼接后的声信号;再次,根据GMM准则将未知雷达目标... 为增加雷达信号的识别方式,提出一种基于雷达信号转换的多维空间声音识别技术。首先,将脉冲式的雷达信号拼接为连续特征声音信号;其次,使用高斯混合模型(Gaussian Mixed Model,GMM)训练拼接后的声信号;再次,根据GMM准则将未知雷达目标转化为特征向量,并与已训练的多维特征向量做对比,得到未知声目标的最大输出概率类型;最后,进行实验分析。实验结果表明,采用基于雷达信号转换的多维空间声音识别技术可以有效识别不同类型的雷达目标,为识别雷达信号提供了一种特殊的识别特征。 展开更多
关键词 雷达目标识别 声目标识别 特征空间
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多维特征空间聚类在工业物料识别中的应用 被引量:1
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作者 吴琼 程文娟 《合肥工业大学学报(自然科学版)》 CAS CSCD 2002年第4期610-613,共4页
在自动识别中 ,往往存在一些不确定的模糊影响因素 ,所以 ,通过聚类算法和模糊理论讨论 ,分析了两者相结合的模糊聚类算法所具有的特点 ,利用多维特征空间的模糊聚类算法对炼钢物料进行识别 ,实验取得了较好的效果 ,其识别正确率达到 92... 在自动识别中 ,往往存在一些不确定的模糊影响因素 ,所以 ,通过聚类算法和模糊理论讨论 ,分析了两者相结合的模糊聚类算法所具有的特点 ,利用多维特征空间的模糊聚类算法对炼钢物料进行识别 ,实验取得了较好的效果 ,其识别正确率达到 92 .5 % 。 展开更多
关键词 特征空间 模糊聚类 工业物料识别 物料特征 炼钢工业 自动识别 图像识别
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融合光谱和时相特征的地表水遥感信息提取方法
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作者 王西营 张帅娟 《内蒙古师范大学学报(自然科学版)》 CAS 2024年第5期488-496,共9页
遥感技术已被广泛应用于大面积地表水观测,但由于水面光谱特征在空间和时间上的高度变化,使得遥感在大面积、多时相地表水监测方面存在局限性,因此提出一种融合光谱和时相特征的地表水遥感信息提取模型,以解决中分辨率遥感影像条件下植... 遥感技术已被广泛应用于大面积地表水观测,但由于水面光谱特征在空间和时间上的高度变化,使得遥感在大面积、多时相地表水监测方面存在局限性,因此提出一种融合光谱和时相特征的地表水遥感信息提取模型,以解决中分辨率遥感影像条件下植被、云、地形阴影等地表覆盖背景中开阔水域的提取问题。基于Google Earth Engine(GEE)平台构建地表水体分类模型系统,处理辅助数据集以及Landsat卫星影像的多光谱/时相属性,从长期连续的Landsat影像多维数据中提取地表水分布,探索干旱地区地表水的时空变化动态。利用三个独立的数据集,验证地表水提取的总体精度和kappa系数分别为0.91和0.81。该模型通用、高效且可靠,应用于中国内陆干旱区的实验表明,该方法对多种环境条件都有效,可为较复杂地表环境下水体提取和时空演化分析提供技术参考。 展开更多
关键词 光谱特征空间 光谱聚簇外壳方程 地表水提取模型 地表水体时空变化
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基于二维极化特征的PolSAR图像决策分类 被引量:3
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作者 邵璐熠 洪文 《雷达学报(中英文)》 CSCD 2016年第6期681-691,共11页
决策树模型在极化SAR数据分类中有着极大的应用价值,既能描述分类结果的极化散射机制,又能获得较好的分类精度。但在对散射机制相似的地物进行分类时,由于经典决策树模型的节点采用的是单个特征,分类精度不理想。因此,该文提出了节点采... 决策树模型在极化SAR数据分类中有着极大的应用价值,既能描述分类结果的极化散射机制,又能获得较好的分类精度。但在对散射机制相似的地物进行分类时,由于经典决策树模型的节点采用的是单个特征,分类精度不理想。因此,该文提出了节点采用2维特征的方法,即在特征集相同的前提下,每次取两个特征组成特征矢量用于节点,提高了经典决策树难以区分的地物的分类精度;并且利用分类结果的混淆矩阵准确定位了导致分类误差的节点,进而对节点进行有针对性的反馈调整,进一步提高了指定地物的分类精度。利用AIRSARFlevoland数据验证了该方法的有效性,并结合极化特征描述了Flevoland地区多种植被的极化散射机制。 展开更多
关键词 决策树 极化特征 2特征空间 混淆矩阵 结果反馈调整
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基于地震灾害场景的主动配电网多维韧性评估方法 被引量:7
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作者 符杨 顾吉平 +2 位作者 田书欣 米阳 刘舒 《电力自动化设备》 EI CSCD 北大核心 2023年第3期1-11,共11页
为了分析主动配电网承受破坏性扰动事件以及快速恢复重要负荷的韧性支撑能力,融合相量测量单元(PMU)高精度动态感知能力提出了一种新的以地震灾害场景为背景的主动配电网多维韧性评估方法。阐述了配电网韧性的基本概念及特征,并将地震... 为了分析主动配电网承受破坏性扰动事件以及快速恢复重要负荷的韧性支撑能力,融合相量测量单元(PMU)高精度动态感知能力提出了一种新的以地震灾害场景为背景的主动配电网多维韧性评估方法。阐述了配电网韧性的基本概念及特征,并将地震作为极端事件代表,构建了反映配电线路故障率与地震动峰值加速度加权均值的模型,继而采用非序贯蒙特卡罗抽样和K-means++聚类算法筛选出代表性的地震场景;基于系统配置的PMU的强感知力建立反映韧性电网应变力、防御力、恢复力和协同力的评估指标,形成韧性多维特征空间,进而利用事件集点簇中心与最优韧性点的加权欧氏距离评估系统多维综合韧性;分析增强电力线路强度、提高联合系统中分布式电源可供容量这2种措施对系统韧性提升的影响,挖掘韧性电网对抗震防灾的学习力。最后,通过改进的PG&E69系统验证所提方法的有效性和准确性。 展开更多
关键词 主动配电网 地震灾害 韧性评估 K-means++聚类 韧性多特征空间
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数据驱动的气动热建模预测方法总结与展望
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作者 王泽 宋述芳 +1 位作者 王旭 张伟伟 《气体物理》 2024年第4期39-55,共17页
气动热的准确预测是指导高超声速飞行器设计的基础。在经典气动热预测方法愈发难以满足工程中高效准确的气动热预测需求的背景下,近年来蓬勃发展的数据驱动气动热建模预测方法逐渐成为气动热预测的新范式。对此,首先阐述了数据驱动气动... 气动热的准确预测是指导高超声速飞行器设计的基础。在经典气动热预测方法愈发难以满足工程中高效准确的气动热预测需求的背景下,近年来蓬勃发展的数据驱动气动热建模预测方法逐渐成为气动热预测的新范式。对此,首先阐述了数据驱动气动热建模预测方法和经典气动热预测方法的相互关系。然后,从建模思路上将数据驱动气动热建模预测方法归纳为3类,即气动热特征空间降维建模预测、气动热逐点建模预测和气动热物理信息嵌入建模预测,并对这3类方法进行了详细介绍和分析总结。数据驱动气动热建模预测方法不仅比工程算法准确,而且和采样方法结合后,还能够有效降低实验测量和数值计算的工作量,给出的模型也更加高效简洁。最后,对数据驱动气动热建模预测方法的发展趋势进行了展望,指出数据驱动技术与经典气动热预测方法的深度结合、气动热物理信息嵌入建模预测方法和气动热预测大模型将会是未来研究的要点。 展开更多
关键词 气动热预测 数据驱动 特征空间 逐点建模 物理信息嵌入
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关于型矩阵的特征值和特征向量的一个说明
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作者 徐怀 汪啸涛 刘保款 《佳木斯大学学报(自然科学版)》 CAS 2016年第4期643-644,共2页
讨论和型矩阵的特征值和特征向量问题。指出和两个矩阵的非零特征值是相同的,且所对应的特征空间的维数也是相同的,并给出特征向量的表达式,最后给出一个数值例子。这些结论的指出丰富了对型矩阵的认识。
关键词 矩阵 特征 特征向量 特征空间
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基于雷达回波极化特征的电力线识别方法 被引量:5
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作者 伍政华 郭锋 +3 位作者 盛匀 顾宗山 姜文东 周啸宇 《雷达科学与技术》 北大核心 2020年第1期63-68,共6页
现有的雷达对电力线的探测能力严重不足,这严重威胁低空飞行器如直升机的飞行安全。研究表明,线状物体对雷达垂直极化和水平极化信号响应强弱具有明显差异性,我们利用回波信号的极化特性建立起多维特征空间,并在该空间内完成电力线目标... 现有的雷达对电力线的探测能力严重不足,这严重威胁低空飞行器如直升机的飞行安全。研究表明,线状物体对雷达垂直极化和水平极化信号响应强弱具有明显差异性,我们利用回波信号的极化特性建立起多维特征空间,并在该空间内完成电力线目标的感知、分类。某在研直升机低空防撞雷达的实测飞行数据表明,在利用极化信息所构建的特征空间内可有效区分电力线目标和虚假目标,准确率达到91%以上。该方法将有利于推动电力线障碍物预警雷达走向实用化。 展开更多
关键词 极化特征 电力线识别 特征空间 障碍物预警雷达
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深度学习下模糊高光谱图像复原数学模型仿真
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作者 苏乐辉 《计算机仿真》 北大核心 2023年第9期167-170,302,共5页
高光谱图像具有三维数据结构,可同时采集目标对象的空间维、光谱维的特征,但其成像过程中,因载荷平台振动,得到高光谱图像较为模糊,影响图像使用中的准确度与可信度。为此,研究一种深度学习下模糊高光谱图像复原数学模型方法。根据高光... 高光谱图像具有三维数据结构,可同时采集目标对象的空间维、光谱维的特征,但其成像过程中,因载荷平台振动,得到高光谱图像较为模糊,影响图像使用中的准确度与可信度。为此,研究一种深度学习下模糊高光谱图像复原数学模型方法。根据高光谱成像原理与点扩散函数求解模糊图像的光谱信息,利用傅里叶变换建立其退化模型,获得模糊图像与实际图像之间相关性。通过3D卷积网络采集模糊图像特征,使用卷积核、激活函数获取特征增加非线性因子,通过反卷积层得到特征图谱,利用图像重建层将特征重组,输出清晰高光谱图像,实现模糊高光谱图像复原。实验结果表明,所提方法能够将模糊图像复原,复原的图像信噪比在6dB以上,且图像复原时间低于15s。 展开更多
关键词 深度学习 卷积核 模糊高光谱图像 退化模型 空间维特征 光谱特征
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Real-time road traffic states estimation based on kernel-KNN matching of road traffic spatial characteristics 被引量:2
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作者 XU Dong-wei 《Journal of Central South University》 SCIE EI CAS CSCD 2016年第9期2453-2464,共12页
The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial charact... The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy. 展开更多
关键词 road traffic kernel function k nearest neighbor (KNN) state estimation spatial characteristics
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基于无人机影像的城市植被精细分类 被引量:8
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作者 林怡 张文豪 +1 位作者 宇洁 张翰超 《中国环境科学》 EI CAS CSCD 北大核心 2022年第6期2852-2861,共10页
针对传统植被资源调查方法工作量大、成本高、效率低的问题,利用高分辨率无人机遥感影像,联合地物光谱-纹理-空间信息,构建了一种适用于描述城市不同植被种类的多维特征空间,在此基础上对三种应用广泛的分类算法(基于像素的、面向对象... 针对传统植被资源调查方法工作量大、成本高、效率低的问题,利用高分辨率无人机遥感影像,联合地物光谱-纹理-空间信息,构建了一种适用于描述城市不同植被种类的多维特征空间,在此基础上对三种应用广泛的分类算法(基于像素的、面向对象的支持向量机及深度学习Mobile-Unet语义分割模型)开展了对比分析研究.结果表明:本文提出的联合地物光谱-纹理-空间信息的特征空间构建方法能够有效地描述城市不同类型植被的特征差异,提升影像分割、植被分类的精度;在分类精度上,基于像素和面向对象的支持向量机分类结果的总体精度均超过90%,深度学习方法的总体分类精度为84%;在算法效率上,传统机器学习方法也优于深度学习方法.因此,得出结论针对城市小区域、小样本的植被精细分类,传统机器学习分类方法比深度学习方法效果更好. 展开更多
关键词 无人机影像 城市植被 精细分类 特征空间 机器学习 深度学习
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Segmentation of High Spatial Resolution Remote Sensing Images of Mountainous Areas Based on the Improved Mean Shift Algorithm 被引量:3
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作者 LU Heng LIU Chao +1 位作者 LI Nai-wen GUO Jia-wei 《Journal of Mountain Science》 SCIE CSCD 2015年第3期671-681,共11页
Using conventional Mean Shift Algorithm to segment high spatial resolution Remote sensing images of mountainous areas usually leads to an unsatisfactory result, due to its rich texture information. In this paper, we p... Using conventional Mean Shift Algorithm to segment high spatial resolution Remote sensing images of mountainous areas usually leads to an unsatisfactory result, due to its rich texture information. In this paper, we propose an improved Mean Shift Algorithm in consideration of the characteristics of these images. First, images were classified into several homogeneous color regions and texture regions by conducting variance detection on the color space. Next, each homogeneous color region was directly segmented to generate the preliminary results by applying the Mean Shift Algorithm. For each texture region, we conduct a high-dimensional feature space by extracting information such as color, texture and shape comprehensively, and work out a proper bandwidth according to the normalized distribution density. Then the bandwidth variable Mean Shift Algorithm was applied to obtain segmentation results by conducting the pattern classification in feature space. Last, the final results were obtained by merging these regions by means of the constructed cost functions and removing the oversegmented regions from the merged regions. It has been experimentally segmented on the high spatial resolution remote sensing images collected by Quickbird and Unmanned Aerial Vehicle(UAV). We put forward an approach to evaluate the segmentation results by using the segmentation matching index(SMI). This takes into consideration both the area and the spectrum. The experimental results suggest that the improved Mean Shift Algorithm outperforms the conventional one in terms of accuracy of segmentation. 展开更多
关键词 Mean Shift Image segmentation Regionmerging UAV image Quickbird image
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基于多Agent的启动装置多类故障高效智能检测 被引量:2
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作者 夏景 《电子设计工程》 2019年第13期7-10,共4页
传统检测方法只能对单个启动装置进行故障检测,无法实现多类故障智能检测,为了避免传统方法带来的弊端,提出了基于多Agent的多类故障高效智能检测方法。根据Agent功能划分结果,从实体状态信息中提取运行行为信息,定时查询相关变量,获取... 传统检测方法只能对单个启动装置进行故障检测,无法实现多类故障智能检测,为了避免传统方法带来的弊端,提出了基于多Agent的多类故障高效智能检测方法。根据Agent功能划分结果,从实体状态信息中提取运行行为信息,定时查询相关变量,获取完整装置运行情况,并将其转化为状态信息。利用已有状态信息建立低维数特征空间,采用等能量分段方法提取相关特征,获取异常状态信息。利用决策Agent模糊理论融合技术对异常状态信息隶属度条件进行设定,获取最可能出现的故障种类,依据高效智能检测流程,实现启动装置多类故障检测。通过实验结果可知,该方法最小检测误差可达到0.005,为电力设备稳定运行奠定基础。 展开更多
关键词 多AGENT 启动装置 多类故障 高效智能检测 特征空间 等能量分段
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KERNEL NEIGHBORHOOD PRESERVING EMBEDDING FOR CLASSIFICATION 被引量:2
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作者 Tao Xiaoyan Ji Hongbing Men Jian 《Journal of Electronics(China)》 2009年第3期374-379,共6页
The Neighborhood Preserving Embedding(NPE) algorithm is recently proposed as a new dimensionality reduction method.However, it is confined to linear transforms in the data space.For this, based on the NPE algorithm, a... The Neighborhood Preserving Embedding(NPE) algorithm is recently proposed as a new dimensionality reduction method.However, it is confined to linear transforms in the data space.For this, based on the NPE algorithm, a new nonlinear dimensionality reduction method is proposed, which can preserve the local structures of the data in the feature space.First, combined with the Mercer kernel, the solution to the weight matrix in the feature space is gotten and then the corresponding eigenvalue problem of the Kernel NPE(KNPE) method is deduced.Finally, the KNPE algorithm is resolved through a transformed optimization problem and QR decomposition.The experimental results on three real-world data sets show that the new method is better than NPE, Kernel PCA(KPCA) and Kernel LDA(KLDA) in performance. 展开更多
关键词 Kernel Neighborhood Preserving Embedding (KNPE) Neighborhood structure FEATUREEXTRACTION QR decomposition
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State Space-Time and Four States of Universe 被引量:5
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作者 Jinzhong Yan 《Journal of Physical Science and Application》 2013年第2期127-134,共8页
All things in the universe possess a state and characteristics of state, resultantly in presence of space-time, which is perceived by human beings. An outlook of space-time is shaped in human by perceiving the existen... All things in the universe possess a state and characteristics of state, resultantly in presence of space-time, which is perceived by human beings. An outlook of space-time is shaped in human by perceiving the existence and change of objects. The state space is all state characteristics exhibited in objects whilst the state time refers to the duration of an object's state. The time is a spatial property and not an independent dimension. The state space-time is a unity of internal and external space-time. The internal space-time is stemmed from the overall internal forces and internal energies and is a covert space-time. The external space-time refers to a space-time manifested by the external characteristics and movement of an object and is an overt space-time. In physics, there are four kinds of forces and four state space-times: bonding force and three-dimensional space-time; strong interaction of exchangeable n meson and two-dimensional space-time; quark confinement and one-dimensional space-time; and weak interaction and zero-dimensional space-time. The universe is constituted by dissimilar state space-times. Newton space-time is a three-dimensional state space-time; Einstein's theory of relativity is a two-dimensional state space-time. Newton and Einstein were different observers. Temporal and spatial perception of human is dependent upon human's intemal energy and quality. Through Qigong exercises, the human is able to enter the three-dimensional, two-dimensional, one-dimensional and zero-dimensional space-times. The relativity theory of human body will solve the time problems at the interplanetary voyage of astronauts. 展开更多
关键词 State space-time UNIVERSE four states.
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Basic Research on Key Techniques Related to Urban 3D Pipe Network Modeling 被引量:1
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作者 DU Guoming GONG Jianya XIONG Hanjiang 《Geo-Spatial Information Science》 2002年第4期41-45,共5页
A new geometric modeling approach is introduced in this paper.First the principle of modeling of 3D pipe network is discussed in detail.Then the procedures of implementing pipe network visualization and system functio... A new geometric modeling approach is introduced in this paper.First the principle of modeling of 3D pipe network is discussed in detail.Then the procedures of implementing pipe network visualization and system functions are presented.Last,several efficient methods for speeding up display of graphics are introduced.The new geometric modeling approach offers to people a new way to solve 3D visualization of complex urban pipe network. 展开更多
关键词 D pipe network VISUALIZATION MODELING
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Recapitulating Quantum Phase Space Representation by Virtue of Normally Ordered Gaussian Form of Wigner Operator
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作者 范洪义 徐兴磊 李洪奇 《Communications in Theoretical Physics》 SCIE CAS CSCD 2010年第2期261-264,共4页
Using the normally ordered Gaussian form of the Wigner operator we recapitulate the quantum phase space representation, we derive a new formula for searching for the classical correspondence of quantum mechanical oper... Using the normally ordered Gaussian form of the Wigner operator we recapitulate the quantum phase space representation, we derive a new formula for searching for the classical correspondence of quantum mechanical operators; we also show that if there exists the eigenvector |q〉λ,v of linear combination of the coordinate and momentum operator, (λQ + vP), where λ,v are real numbers, and |q〉λv is complete, then the projector |q〉λ,vλ,v〈q| must be the Radon transform of Wigner operator. This approach seems concise and physical appealing. 展开更多
关键词 IWOP technique normally ordered Gaussian form of the Wigner operator Weyl correspondenceand Weyl ordering
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Fault Diagnosis Based on MultiKernel Classification and Information Fusion Decision
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作者 Mohammad Reza Vazifeh Pan Hao Farzaneh Abbasi 《Computer Technology and Application》 2013年第8期404-409,共6页
In machine learning and statistics, classification is the a new observation belongs, on the basis of a training set of data problem of identifying to which of a set of categories (sub-populations) containing observa... In machine learning and statistics, classification is the a new observation belongs, on the basis of a training set of data problem of identifying to which of a set of categories (sub-populations) containing observations (or instances) whose category membership is known. SVM (support vector machines) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. The basic SVM takes a set of input data and predicts, for each given input, which of two possible classes fon^as the output, making it a non-probabilistic binary linear classifier. In pattern recognition problem, the selection of the features used for characterization an object to be classified is importance. Kernel methods are algorithms that, by replacing the inner product with an appropriate positive definite function, impticitly perform a nonlinear mapping 4~ of the input data in Rainto a high-dimensional feature space H. Cover's theorem states that if the transformation is nonlinear and the dimensionality of the feature space is high enough, then the input space may be transformed into a new feature space where the patterns are linearly separable with high probability. 展开更多
关键词 Fault diagnosis wavelet-kernel information fusion multi classification.
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Kernelized fourth quantification theory for mineral target prediction
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作者 CHEN Yongliang LI Xuebin LIN Nan 《Global Geology》 2011年第4期265-278,共14页
This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantifica- tion theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal w... This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantifica- tion theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal with the problem of mineral prediction without defining a training area. In mineral target prediction, the pre-defined statistical cells, such as grid cells, can be implicitly transformed using kernel techniques from input space to a high-dimensional feature space, where the nonlinearly separable clusters in the input space are ex- pected to be linearly separable. Then, the transformed cells in the feature space are mapped by the fourth quan- tifieation theory onto a low-dimensional scaling space, where the sealed cells can be visually clustered according to their spatial locations. At the same time, those cells, which are far away from the cluster center of the majority of the sealed cells, are recognized as anomaly cells. Finally, whether the anomaly cells can serve as mineral potential target cells can be tested by spatially superimposing the known mineral occurrences onto the anomaly ceils. A case study shows that nearly all the known mineral occurrences spatially coincide with the anomaly cells with nearly the smallest scaled coordinates in one-dimensional sealing space. In the case study, the mineral target cells delineated by the new model are similar to those predicted by the well-known WofE model. 展开更多
关键词 kernel function feature space fourth quantification theory nonlinear transformation mineral target prediction
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关于有界水团混合的讨论
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作者 徐斯 王锡候 王仁树 《山东海洋学院学报》 1985年第C00期286-286,共1页
本文首次从理论上将国外一组无界水团的混合模型,推广到三维有界水团混合的普遍模型;提出了根据T—S二维特征空间序偶的分布特征,进行海洋水团识别的几何学方法,促进了水团分析由定性向定量的过渡。
关键词 有界水团 混合模型 T—S二特征空间 序偶 分布特征
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