助手标题  
全文文献 工具书 数字 学术定义 翻译助手 学术趋势 更多
查询帮助
意见反馈
   geological variable 在 矿业工程 分类中 的翻译结果: 查询用时:0.064秒
图标索引 在分类学科中查询
所有学科
矿业工程
地质学
自然地理学和测绘学
计算机软件及计算机应用
数学
地球物理学
环境科学与资源利用
更多类别查询

图标索引 历史查询
 

geological variable    
相关语句
  地质变量
    ESTIMATION OF FRACTAL DIMENSION FOR QUALITATIVE GEOLOGICAL VARIABLE AND MICRO—GEOLOGICAL ANOMALY
    定性地质变量分维数估计与显微地质异常
短句来源
    and metallogenic or ore-controlling geological variables (quantitative geological variable, qualitive variable and semiquantitative variable). The signiticances of geological variables are measured by τ -rank coefficients of geological variables and objective variable. The potentials of mineral resources targets are measured by relativities of ore deposit cells.
    该方法以评价目标变量(矿床的资源量、矿床规模等)与成矿和控矿地质变量(定量地质变量、半定量地质变量和定性地质变量)之间的秩相关性研究为基础,用地质变量与目标变量之间的τ秩相关系数来衡量地质变量的重要程度,用矿床统计单元之间的联系度来评价资源靶区的优劣
短句来源
    The deficiency of traditional estimating method which is used to build coal bed geological model is analyzed. The theory and method of neural network, and the feasibility and superiority of building the coal bed geological model are also discussed by considering the geological variable characteristics, such as space territory, continuity, anisotropism and great non liner relation. The neural network used to estimate the geological variables is built, and the non liner mapping relation between geological variables and their influence factors is described also.
    分析了建立矿床地质模型传统的估值方法的不足 ,针对地质变量之间具有空间局域性、连续性和各向异性 ,以及高度非线性关系的特征 ,阐述了应用人工神经网络原理和方法建立矿床地质模型的可能性和优越性 ,建立了地质变量参数估值计算的神经网络模型的基本结构 ,描述了地质变量与其影响因素之间的非线性映射关系 ,从而提出了基于人工神经网络原理的地质模型估值方法
短句来源
    The process and method of development of ore predictive system based on geographic information system and artificial neural network,with automatic processing from optimization of geological variable to graphical display of metallogenic prognosis,are described in this paper, design schedule of the system is put forward, sub-systems of database management, GIS and ANN ore prediction are introduced and technical requirements for realization of the system are briefly showed.
    利用地理信息系统(GIS)和人工神经网络(ANN)相结合,提出的基于GIS的人工神经网络矿产预测系统设计方案,实现了从地质变量优选到人工神经网络成矿预测结果图形显示的计算机自动化处理。 其中的主要模块为:地质变量优选模块、数据库管理模块、神经网络成矿预测模块和图形处理功能模块。
短句来源
    The process and method of development of ore predictive system based on geographic information system and artificial neural network ,with automatic processing from optimization of geological variable to graphical display of metallogenic prognosis,are described in this paper, design schedule of the system is put forward, sub-systems of database management ,GIS and ANN ore prediction are introduced and technical requirements for realization of the system are briefly shown.
    将地理信息系统(GIS)和人工神经网络(ANN)相结合,提出基于GIS的人工神经网络矿产预测系统设计方案,实现了从地质变量优选到人工神经网络成矿预测结果图形显示的计算机自动化处理,并对其中的主要模块:地质变量优选模块、数据库管理模块和神经网络成矿预测模块进行了介绍,简要说明了各模块功能实现中所应用的主要技术。
短句来源
  地质变量
    ESTIMATION OF FRACTAL DIMENSION FOR QUALITATIVE GEOLOGICAL VARIABLE AND MICRO—GEOLOGICAL ANOMALY
    定性地质变量分维数估计与显微地质异常
短句来源
    and metallogenic or ore-controlling geological variables (quantitative geological variable, qualitive variable and semiquantitative variable). The signiticances of geological variables are measured by τ -rank coefficients of geological variables and objective variable. The potentials of mineral resources targets are measured by relativities of ore deposit cells.
    该方法以评价目标变量(矿床的资源量、矿床规模等)与成矿和控矿地质变量(定量地质变量、半定量地质变量和定性地质变量)之间的秩相关性研究为基础,用地质变量与目标变量之间的τ秩相关系数来衡量地质变量的重要程度,用矿床统计单元之间的联系度来评价资源靶区的优劣
短句来源
    The deficiency of traditional estimating method which is used to build coal bed geological model is analyzed. The theory and method of neural network, and the feasibility and superiority of building the coal bed geological model are also discussed by considering the geological variable characteristics, such as space territory, continuity, anisotropism and great non liner relation. The neural network used to estimate the geological variables is built, and the non liner mapping relation between geological variables and their influence factors is described also.
    分析了建立矿床地质模型传统的估值方法的不足 ,针对地质变量之间具有空间局域性、连续性和各向异性 ,以及高度非线性关系的特征 ,阐述了应用人工神经网络原理和方法建立矿床地质模型的可能性和优越性 ,建立了地质变量参数估值计算的神经网络模型的基本结构 ,描述了地质变量与其影响因素之间的非线性映射关系 ,从而提出了基于人工神经网络原理的地质模型估值方法
短句来源
    The process and method of development of ore predictive system based on geographic information system and artificial neural network,with automatic processing from optimization of geological variable to graphical display of metallogenic prognosis,are described in this paper, design schedule of the system is put forward, sub-systems of database management, GIS and ANN ore prediction are introduced and technical requirements for realization of the system are briefly showed.
    利用地理信息系统(GIS)和人工神经网络(ANN)相结合,提出的基于GIS的人工神经网络矿产预测系统设计方案,实现了从地质变量优选到人工神经网络成矿预测结果图形显示的计算机自动化处理。 其中的主要模块为:地质变量优选模块、数据库管理模块、神经网络成矿预测模块和图形处理功能模块。
短句来源
    The process and method of development of ore predictive system based on geographic information system and artificial neural network ,with automatic processing from optimization of geological variable to graphical display of metallogenic prognosis,are described in this paper, design schedule of the system is put forward, sub-systems of database management ,GIS and ANN ore prediction are introduced and technical requirements for realization of the system are briefly shown.
    将地理信息系统(GIS)和人工神经网络(ANN)相结合,提出基于GIS的人工神经网络矿产预测系统设计方案,实现了从地质变量优选到人工神经网络成矿预测结果图形显示的计算机自动化处理,并对其中的主要模块:地质变量优选模块、数据库管理模块和神经网络成矿预测模块进行了介绍,简要说明了各模块功能实现中所应用的主要技术。
短句来源
  地质变量的
    and metallogenic or ore-controlling geological variables (quantitative geological variable, qualitive variable and semiquantitative variable). The signiticances of geological variables are measured by τ -rank coefficients of geological variables and objective variable. The potentials of mineral resources targets are measured by relativities of ore deposit cells.
    该方法以评价目标变量(矿床的资源量、矿床规模等)与成矿和控矿地质变量(定量地质变量、半定量地质变量和定性地质变量)之间的秩相关性研究为基础,用地质变量与目标变量之间的τ秩相关系数来衡量地质变量的重要程度,用矿床统计单元之间的联系度来评价资源靶区的优劣
短句来源
  地质变量
    ESTIMATION OF FRACTAL DIMENSION FOR QUALITATIVE GEOLOGICAL VARIABLE AND MICRO—GEOLOGICAL ANOMALY
    定性地质变量分维数估计与显微地质异常
短句来源
    and metallogenic or ore-controlling geological variables (quantitative geological variable, qualitive variable and semiquantitative variable). The signiticances of geological variables are measured by τ -rank coefficients of geological variables and objective variable. The potentials of mineral resources targets are measured by relativities of ore deposit cells.
    该方法以评价目标变量(矿床的资源量、矿床规模等)与成矿和控矿地质变量(定量地质变量、半定量地质变量和定性地质变量)之间的秩相关性研究为基础,用地质变量与目标变量之间的τ秩相关系数来衡量地质变量的重要程度,用矿床统计单元之间的联系度来评价资源靶区的优劣
短句来源
    The deficiency of traditional estimating method which is used to build coal bed geological model is analyzed. The theory and method of neural network, and the feasibility and superiority of building the coal bed geological model are also discussed by considering the geological variable characteristics, such as space territory, continuity, anisotropism and great non liner relation. The neural network used to estimate the geological variables is built, and the non liner mapping relation between geological variables and their influence factors is described also.
    分析了建立矿床地质模型传统的估值方法的不足 ,针对地质变量之间具有空间局域性、连续性和各向异性 ,以及高度非线性关系的特征 ,阐述了应用人工神经网络原理和方法建立矿床地质模型的可能性和优越性 ,建立了地质变量参数估值计算的神经网络模型的基本结构 ,描述了地质变量与其影响因素之间的非线性映射关系 ,从而提出了基于人工神经网络原理的地质模型估值方法
短句来源
    The process and method of development of ore predictive system based on geographic information system and artificial neural network,with automatic processing from optimization of geological variable to graphical display of metallogenic prognosis,are described in this paper, design schedule of the system is put forward, sub-systems of database management, GIS and ANN ore prediction are introduced and technical requirements for realization of the system are briefly showed.
    利用地理信息系统(GIS)和人工神经网络(ANN)相结合,提出的基于GIS的人工神经网络矿产预测系统设计方案,实现了从地质变量优选到人工神经网络成矿预测结果图形显示的计算机自动化处理。 其中的主要模块为:地质变量优选模块、数据库管理模块、神经网络成矿预测模块和图形处理功能模块。
短句来源
    The process and method of development of ore predictive system based on geographic information system and artificial neural network ,with automatic processing from optimization of geological variable to graphical display of metallogenic prognosis,are described in this paper, design schedule of the system is put forward, sub-systems of database management ,GIS and ANN ore prediction are introduced and technical requirements for realization of the system are briefly shown.
    将地理信息系统(GIS)和人工神经网络(ANN)相结合,提出基于GIS的人工神经网络矿产预测系统设计方案,实现了从地质变量优选到人工神经网络成矿预测结果图形显示的计算机自动化处理,并对其中的主要模块:地质变量优选模块、数据库管理模块和神经网络成矿预测模块进行了介绍,简要说明了各模块功能实现中所应用的主要技术。
短句来源

 

查询“geological variable”译词为其他词的双语例句

 

查询“geological variable”译词为用户自定义的双语例句

    我想查看译文中含有:的双语例句
例句
为了更好的帮助您理解掌握查询词或其译词在地道英语中的实际用法,我们为您准备了出自英文原文的大量英语例句,供您参考。
  geological variable
In addition, the experimental PCSVs provide basic information about the heterogeneity of the geological variable in the region, and furthermore many useful interpretations can be made concerning the regional variability of the variable.
      
In order to avoid these problems, a special type of geological variable, referred to as the target variable appears in a favorability equation.
      


The authors of this paper proposed a new statistical method so called rank correlation weight method used for locative prediction of mineral resources targets. This method is based on rank correlation of objective variables (quantity of mineral resourcs, metallogenic size, etc.) and metallogenic or ore-controlling geological variables (quantitative geological variable, qualitive variable and semiquantitative variable). The signiticances of geological variables are measured by τ -rank coefficients...

The authors of this paper proposed a new statistical method so called rank correlation weight method used for locative prediction of mineral resources targets. This method is based on rank correlation of objective variables (quantity of mineral resourcs, metallogenic size, etc.) and metallogenic or ore-controlling geological variables (quantitative geological variable, qualitive variable and semiquantitative variable). The signiticances of geological variables are measured by τ -rank coefficients of geological variables and objective variable. The potentials of mineral resources targets are measured by relativities of ore deposit cells.

提出了一种矿产资源靶区定位预测的统计方法秩相关权法。该方法以评价目标变量(矿床的资源量、矿床规模等)与成矿和控矿地质变量(定量地质变量、半定量地质变量和定性地质变量)之间的秩相关性研究为基础,用地质变量与目标变量之间的τ秩相关系数来衡量地质变量的重要程度,用矿床统计单元之间的联系度来评价资源靶区的优劣

The deficiency of traditional estimating method which is used to build coal bed geological model is analyzed. The theory and method of neural network, and the feasibility and superiority of building the coal bed geological model are also discussed by considering the geological variable characteristics, such as space territory, continuity, anisotropism and great non liner relation. The neural network used to estimate the geological variables is built, and the non liner mapping relation between geological...

The deficiency of traditional estimating method which is used to build coal bed geological model is analyzed. The theory and method of neural network, and the feasibility and superiority of building the coal bed geological model are also discussed by considering the geological variable characteristics, such as space territory, continuity, anisotropism and great non liner relation. The neural network used to estimate the geological variables is built, and the non liner mapping relation between geological variables and their influence factors is described also. Thereby the estimating method of geological model based on neural network is brought forward.

分析了建立矿床地质模型传统的估值方法的不足 ,针对地质变量之间具有空间局域性、连续性和各向异性 ,以及高度非线性关系的特征 ,阐述了应用人工神经网络原理和方法建立矿床地质模型的可能性和优越性 ,建立了地质变量参数估值计算的神经网络模型的基本结构 ,描述了地质变量与其影响因素之间的非线性映射关系 ,从而提出了基于人工神经网络原理的地质模型估值方法

The process and method of development of ore predictive system based on geographic information system and artificial neural network,with automatic processing from optimization of geological variable to graphical display of metallogenic prognosis,are described in this paper, design schedule of the system is put forward, sub-systems of database management, GIS and ANN ore prediction are introduced and technical requirements for realization of the system are briefly showed.

利用地理信息系统(GIS)和人工神经网络(ANN)相结合,提出的基于GIS的人工神经网络矿产预测系统设计方案,实现了从地质变量优选到人工神经网络成矿预测结果图形显示的计算机自动化处理。其中的主要模块为:地质变量优选模块、数据库管理模块、神经网络成矿预测模块和图形处理功能模块。它们之间通过数据库进行数据传输与共享达到互相连接。

 
<< 更多相关文摘    
图标索引 相关查询

 


 
CNKI小工具
在英文学术搜索中查有关geological variable的内容
在知识搜索中查有关geological variable的内容
在数字搜索中查有关geological variable的内容
在概念知识元中查有关geological variable的内容
在学术趋势中查有关geological variable的内容
 
 

CNKI主页设CNKI翻译助手为主页 | 收藏CNKI翻译助手 | 广告服务 | 英文学术搜索
版权图标  2008 CNKI-中国知网
京ICP证040431号 互联网出版许可证 新出网证(京)字008号
北京市公安局海淀分局 备案号:110 1081725
版权图标 2008中国知网(cnki) 中国学术期刊(光盘版)电子杂志社