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1) weighted Mahalanobis distance
加权马氏距离
1.
This study analyzes the issue of multi-response product design using the method of weighted Mahalanobis distance and points out a problem with this method.
分析了用加权马氏距离法进行多响应产品设计的问题,指出了该方法应用过程中存在的问题,并且提供了这种问题的数学解释;同时提出了一个简单的避免方法,这种方法还可以辅助进行权值的设定,能够在一定程度上减少权值确定中的主观因素。
2) Weighted Mahalanobis Distance (FWMD) method
模糊加权马氏距离
3) Weighted Mahalanobis Distance(WMD)
权重马氏距离
1.
To obtain a better segmentation result,this paper used Weighted Mahalanobis Distance(WMD) Gaussian kernel for Nystrm-Ncut segmentation.
为了使经典谱分割的Nystrm采样快速算法得到更清晰的结果,将权重马氏距离高斯核应用于其中,相对于常用的马氏距离高斯核,得到了更好的分割效果。
4) Euclid distance with weights
加权欧氏距离
1.
However, to apply Euclid distance with weights, we need know the actual meaning of the data and the analyst must have relative professional knowledge.
聚类是数据挖掘的一种常用技术,最常用的距离度量方法是欧几里得距离,但运用加权欧氏距离需要对数据的实际意义有一定了解,并且要求分析者具有相关的专业知识,而在实际操作中这一点很难保证。
2.
Takes the research example by 37 natural science journals of normal university of China,a model of evaluation of the academic quality of sci-tech periodicals using Euclid distance with weights is established.
以我国37种师范大学自然科学版学报为研究实例,建立了利用加权欧氏距离评价科技期刊学术质量的模型,该评价模型简单、实用,为科技期刊的学术质量评价提供了一种新方法。
5) weighted Euclidean distance
加权欧氏距离
1.
A speech emotion recognition method is also presented based on weighted Euclidean distance template matching, in which the weights of features are calculated by the method of contribution analysis.
同时提出采用贡献分析法确定情感特征参数的权值,利用加权欧氏距离模板匹配识别语音情感。
2.
The pape establishes nonlinear programming model to calculate weight value of risk s attributes under the condition of incomplete weight information, and evaluate the risk by seeking weighted Euclidean distance, solve the problem that the opinions can not be unified because of different knowledge, experiences and preferences.
本文使用多属性决策方法进行供应链风险评估,在风险属性权重信息不完全的情况下,建立非线性规划模型求得各风险属性的权重值,并通过求与理想解之间的加权欧氏距离来评估风险值的大小,解决了评估专家由于知识、经验和偏好不完全相同而意见难以统一的困难,最后用一个例子说明了该方法的有效性和实用性。
6) Hamming Distance with weight
加权明氏距离
补充资料：权氏
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