1) attribute-weight analysis
属性权重分析
1.
The paper also discusses the research on project case and task representation,and case retrieval and matching using combination of the attribute-weight analysis and K-nearest neighbor(KNN) method.
基于案例推理方法的基本原理,将案例推理方法应用于项目管理辅助决策支持分析,论述了基于案例推理的项目管理决策支持系统中的一些关键步骤,研究了项目管理中项目任务问题案例的知识案例表达、属性权重分析和近邻方法相结合的检索模型,实现了案例检索和匹配,提出了辅助项目任务问题案例辅助决策支持系统的结构,开发了原型系统,并给出应用实例。
2) attribute weight
属性权重
1.
The attribute weight and weighted support of default regular are defined by using the conditional entropy and a mining algorithm of default regulars are given for inconsistent database.
针对不一致数据库,定义属性权重及缺省规则加权支持度概念,在此基础上给出一种缺省规则挖掘算法。
2.
With respect to the problem of multiple attribute decision-making with incomplete information on attribute weights to which the attribute values are given in terms of interval numbers, a modified TOPSIS (technique for order preference by similarity to ideal solution) analysis is proposed.
针对属性权重信息不完全且属性值以区间数形式给出的多属性决策问题,提出了一种逼近于理想点(TOPSIS)的决策分析方法。
3.
With regard to the problem of determining attribute weights in uncertain multiple attribute decision making, in which the attribute values are in form of interval number, a new method is proposed to determine interval entropy weights.
针对属性值以区间数形式给出的不确定性多属性决策中确定属性权重的问题,提出了一种区间数熵权的确定方法·依据多属性决策中传统熵权确定方法的思路,首先,通过构建两个最优化模型,求得区间熵;然后根据传统熵权确定公式及区间数运算法则得到以区间数形式表示的属性熵权·该方法具有概念清晰、实用的特点,得出的属性熵权能够较好地反映各属性信息的差异程度·最后通过一个算例说明了该方法的实用性和有效性
3) attribute weights
属性权重
1.
A method of entropy for obtaining the attribute weights of interval numbers decision-making matrix;
确定区间数决策矩阵属性权重的方法——熵值法
2.
A method was presented to deal with the fuzzy multiple attribute decision making problem with preference values on alternatives,in which the attribute weights were unknown completely and the attribute values and preference values are fuzzy variables.
针对属性值均为模糊变量,属性权重完全未知但给出方案偏好值的模糊多属性决策问题给出了决策方法。
3.
The purpose of this paper is to research the bipartite matching problem with incomplete attribute weights in consumer to consumer(C2C) e-commerce environment.
以C2C电子商务为实际背景,研究了在商品属性权重信息不完全的情况下买卖双方的双边匹配问题。
4) weight analysis
权重分析
1.
The approach is based on the weight analysis of BP network.
将BP网络权重分析法与其它源解析法应用于实例进行分析比较,结果表明:BP网络权重分析用于大气颗粒物源解析意义明确,方法简便可行。
2.
The BP model structure of two hidden layers and three inputs in the study catchment was determined by the neural network weight analysis.
本文利用普定后寨河流域实测降雨、径流系列资料,采用神经网络权重分析法确定该流域的人工神经网络模型结构为两个隐含层、三个输入变量,该人工神经网络模型结构可以保持降雨-径流模拟的稳定性。
5) coordinate analysis of center of attribute gravity
属性重心坐标分析法
6) attribute analysis
属性分析
1.
Problems in thin-layer attribute analysis and solved methods-a case study in beach bar sandstones in Liang108 area of Dongying Sag;
薄层属性分析中存在的问题及解决方法——以东营凹陷梁108地区滩坝砂岩为例
2.
The method of attribute analysis in non-optimum to optimum;
从非优到优的属性分析方法
3.
Application of seismic attribute analysis in Shengli exploration area.;
地震属性分析及其在胜利探区的应用
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参考词条