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fuzzy weights of evidence
相关语句
  模糊证据权重
     In this paper, two methods for spatial integration and decision making are discussed. One is fuzzy weights of evidence, and the other is weighted logistic regression.
     本文讨论两个空间数据集成和决策支持方法:模糊证据权重和加权逻辑回归方法。
短句来源
  “fuzzy weights of evidence”译为未确定词的双语例句
     Application of Fuzzy Weights of Evidence Method in Mineral Resource Assessment for Gold in Zhenyuan District, Yunnan Province, China
     模糊证据权方法在镇沅(老王寨)地区金矿资源评价中的应用
短句来源
     GeoData Integration and Spatial Decision Making Based on Fuzzy Weights of Evidence and Weighted Logistic Regression
     地学数据集成及空间决策支持的方法与应用
短句来源
     This paper proposes an extended version of the fuzzy weights of evidence method, based on the fuzzy training layer for assessing and predicting the occurrence of area-events.
     为了使在地理信息系统中被广泛用于点事件预测的证据权方法能对面事件进行评价和预测,提出了一种新的基于模糊训练层的证据权方法.
短句来源
     When both evidence and training data are fuzzy sets, the new method acts as a dual fuzzy weights of evidence method.
     该方法可以处理训练层和证据层均为模糊集合的情况,被称为双重模糊证据权方法.
短句来源
     16 targeting areas were delineated using fuzzy weights of evidence method and were suggested for further exploration. The detailed comparison of fuzzy weights of evidence method with the ordinary weights of evidence method shows that the former can produce better results with less loss of useful information during construction of discrete evidential layers.
     对比普通证据权方法与模糊证据权方法所得结果表明,模糊证据权方法可减小图层离散化造成的有用信息损失,提高预测结果精度.
短句来源
  相似匹配句对
     Weights optimization based on fuzzy reasoning
     基于模糊推理的权重优化
短句来源
     Fuzzy Weights and Rank-Ordering of Projects
     模糊权数与方案排序
短句来源
     Fuzzy C Mean Algorithm Based on Feature Weights
     基于属性权重的Fuzzy C Mean算法
短句来源
     Application of DEA Model with Fuzzy Restriction on Weights
     模糊权重约束的DEA模型及其应用
短句来源
     Consistence of the Judgement Matrix and Ordering of Weights in Fuzzy AHP
     模糊判断矩阵的一致性及权重排序
短句来源
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  fuzzy weights of evidence
Fuzzy Weights of Evidence Method and Its Application in Mineral Potential Mapping
      


How to integrate quantitative data, qualitative data, empirical data and knowledge-based data and then make decision is one of the important issues in spatial data analysis. In this paper, two methods for spatial integration and decision making are discussed. One is fuzzy weights of evidence, and the other is weighted logistic regression. Compared with the traditional methods such as discriminate analysis and multivariate regression analysis, these two methods can give more reasonable results when explanatory...

How to integrate quantitative data, qualitative data, empirical data and knowledge-based data and then make decision is one of the important issues in spatial data analysis. In this paper, two methods for spatial integration and decision making are discussed. One is fuzzy weights of evidence, and the other is weighted logistic regression. Compared with the traditional methods such as discriminate analysis and multivariate regression analysis, these two methods can give more reasonable results when explanatory variables are a mixed mode of continuous and category data.

空间数据分析技术的严重滞后出现了“信息爆炸”的现象。因此,由于地学数据多源性的特点,如何集成量纲不一,形式多样,既有定量数据,又有定性的文字描述,经验性和知识性的地学数据并使之帮助决策成为当前亟待研究的课题之一。本文讨论两个空间数据集成和决策支持方法:模糊证据权重和加权逻辑回归方法。与传统地学数据集成和空间决策支持方法如判别分析和其他多元回归不同之处在于,这两种方法在解释变量是连续和类别变量混合模式的情况下或响应变量取两类值的情况下处理的结果更为合理。

This paper proposes an extended version of the fuzzy weights of evidence method, based on the fuzzy training layer for assessing and predicting the occurrence of area-events. It can be considered as a generalization of the ordinary weights of evidence method, which is used to predict the occurrence of point-events with known evidences and training layers. Unlike the ordinary weights of evidence using point training sets, the new method involves training data as a fuzzy...

This paper proposes an extended version of the fuzzy weights of evidence method, based on the fuzzy training layer for assessing and predicting the occurrence of area-events. It can be considered as a generalization of the ordinary weights of evidence method, which is used to predict the occurrence of point-events with known evidences and training layers. Unlike the ordinary weights of evidence using point training sets, the new method involves training data as a fuzzy set. Point training data can be converted to a fuzzy set, therefore the new method can predict both point-events and area-events. When both evidence and training data are fuzzy sets, the new method acts as a dual fuzzy weights of evidence method. A case study has been used to demonstrate the application of the method in assessing desertification in the area in the contact of Shanxi and Shaanxi Provinces and Inner Mongolia Autonomous Region.

为了使在地理信息系统中被广泛用于点事件预测的证据权方法能对面事件进行评价和预测,提出了一种新的基于模糊训练层的证据权方法.它是一种更广泛的证据权方法,与普通证据权方法所不同的是,它的训练层是模糊集合,其取值是它的隶属度.通过适当的变换也可以把点训练层转换为模糊集合.因此,该方法可以对面事件、点事件和线事件进行评价和预测.该方法可以处理训练层和证据层均为模糊集合的情况,被称为双重模糊证据权方法.作为该方法的一个应用实例,本文介绍毛乌素沙漠边缘的晋陕蒙地区土地沙漠化评价的应用实例.

The fuzzy weights of evidence method implemented in GeoDAS GIS was applied to delineate targets for exploration of gold mineral deposits in Zhenyuan mineral district, Yunnan Province, southwestern China. According to the mineral deposit model compiled by USGS, the mineral deposit type discovered in the area is determined as mesothermal gold deposit. Together with field observations the mineralization associated elements are determined, which include Au, As, Hg, Ag, Sb, Pb, and Cd. The singularity method...

The fuzzy weights of evidence method implemented in GeoDAS GIS was applied to delineate targets for exploration of gold mineral deposits in Zhenyuan mineral district, Yunnan Province, southwestern China. According to the mineral deposit model compiled by USGS, the mineral deposit type discovered in the area is determined as mesothermal gold deposit. Together with field observations the mineralization associated elements are determined, which include Au, As, Hg, Ag, Sb, Pb, and Cd. The singularity method and S-A methods provided in GeoDAS GIS were applied to delineate the weak anomalies and mixing anomalies related to gold mineral deposits. Principal component analysis method was utilized to analyze these elements to form two components (PC2 and PC3) which may reflect two different types of mineralization: PC2 dominated by Au-As-Hg-Co-Ni-Cu may be related to mesothermal deposits formed close to the contact of the ultramafic intrusions; whereas the PC3 dominated by Au-As-Hg-Ag-Pb may represent epithermal mineral deposits located in the sedimentary basin away from the ultramafic intrusions. The peaks of scores on these types of composite anomaly maps were delineated and used as training points for utilization of weights of evidence method and fuzzy weights of evidence method, respectively. 16 targeting areas were delineated using fuzzy weights of evidence method and were suggested for further exploration. The detailed comparison of fuzzy weights of evidence method with the ordinary weights of evidence method shows that the former can produce better results with less loss of useful information during construction of discrete evidential layers.

采用模糊证据权方法和GeoDASGIS技术开展了镇沅(老王寨)及其邻区的金矿资源潜力评价.分别采用GeoDASGIS软件提供的局部奇异性分析技术、S-A异常分解技术、主成分分析技术、证据权、模糊证据权等技术对相关地球化学元素进行了系统的处理和分析.应用主成分分析方法确定了可能的2种不同成矿类型,并采用主成分得分确定了组合异常点,在此基础上分别采用普通证据权和模糊证据权方法编制了成矿后验概率图,圈定了有利成矿地段.对比普通证据权方法与模糊证据权方法所得结果表明,模糊证据权方法可减小图层离散化造成的有用信息损失,提高预测结果精度.

 
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