区间数比较大小可以有很多方法。
提出了区间数的相对左偏度的定义。
We put forth the definition of left deviation degree of interval number.
文章提出了两种处理区间数的方法。
Two methods to treat the interval cost estimates have been proposed.
广义区间数的算术四则运算有广泛应用。
The arithmetic operation of the general interval Numbers has wide applications.
区间数的乘法是较难的。
定义了区间数据包络分析(DEA)模型。
An interval data envelopment analysis (DEA) model was first defined.
研究群组区间数互补判断矩阵偏好信息的集结问题。
The aggregation problem about the group preference information of interval number complementary judgement matrices is researched.
基于区间数比较的可能度公式，提出了准一致性概念。
On the basis of the possibility degree for ranking interval numbers, a new concept—the quasi-consistency is proposed.
这也证明了应用区间数学来描述误差和公差是正确的。
Therefore, it also proves that it is correct to apply interval mathematics to describe error and tolerance.
讨论了属性值为区间数的一类不确定性多属性决策问题。
The uncertain multi-attribute decision making problem in which the attribute values are interval numbers is discussed.
研究区间数互反判断矩阵和区间数互补判断矩阵的集结。
The group aggregation approach of interval number reciprocal comparison matrix and interval number complementary comparison matrix is studied.
给出了求可能有效解的方法，并对区间数线性规划进行拓展。
An approach to obtaining possible effective solution is proposed and an extension of interval number linear programming is given.
以区间数学为理论基础，提出了结构灵敏度分析的区间方法。
Based on interval mathematics, an interval method for sensitivity analysis of the structures was proposed.
首先，给出了区间数一致性互反判断矩阵、相对优势度等概念。
Firstly, some concepts, such as interval Numbers consistent reciprocal judgment matrix, relative superiority degree, etc, are given.
研究了实数、区间数和模糊数相结合的混合型多属性决策问题。
This paper investigates a hybrid multiple attribute decision making problem with real number and fuzzy number.
本文提出基于指标均衡和权重区间数的供应链合作伙伴选择方法。
This paper presents a method for partner selection in supply chain based on index equilibrium and power interval Numbers.
因此研究区间数多属性决策问题具有重要的理论意义和应用价值。
Therefore, the research of multi-attribute decision making problem of interval Numbers has important theoretical significance and practical application value.
以区间数学为理论基础，提出了作战效能灵敏度分析的区间方法。
An interval method was proposed for sensitivity analysis of operational effectiveness based on interval mathematics.
结果表明，该方法是集结区间数判断矩阵群信息最有效的方法之一。
The result showed that the method was one of the most effective methods for aggregating group information under interval-number judgment matrixes.
区间分析法是基于区间数学和泰勒展开的一种处理不确定性的方法。
Based on interval mathematics and Taylor series expansion, the interval analysis method is used to deal with uncertainties.
针对具有区间数的多指标决策问题，提出了一种新的决策分析方法。
With respect to multiple attribute decision making problems with intervals, a new decision analysis method is proposed.
针对具有区间数的信息系统，提出用粗糙神经网络求解其问题的方法。
A rough neural network method is proposed to solve the problems in an information system with interval Numbers.
引入一种反映决策者心态的指标，并以此给出区间数的一种排序方法。
The method of ranking interval Numbers is presented by introducing an index to reflect decision-maker's attitude.
运用格序决策理论对区间数的排序问题进行研究，提出了一种新方法。
This paper investigates the problem of interval ranking by lattice order decision making theory, a new method is proposed.
为了简化计算，把区间数和模糊数转化成精确数得到规范的决策矩阵。
For easing computation, we turn interval numbers and fuzzy numbers into precise numbers.
基于区间数层次分析法研究大型钢铁企业关键备件——轧辊供应商评价。
The problem of the key spare-roll vendor selection for the large-scale iron-steel enterprise is studied based on the interval numbers analytic hierarchy process.
研究结果表明，如果销售量和分段区间数既定，则最优固定折扣率存在。
The result shows that if the selling volume and the intervals into which the selling volume is divided are set, the optimal fixed discount rate exists.
研究了属性权重和属性值均以区间数形式给出的不确定多属性决策问题。
The uncertain multiple attribute decision-making problem is discussed, in which the attribute weights and the attribute values are in the forms of interval Numbers.
符号聚类是对传统聚类的重要扩展，而区间数据是一类常见的符号数据。
Clustering for symbolic data is an important extension of conventional clustering, and interval representation for symbolic data is often used.
符号聚类是对传统聚类的重要扩展，而区间数据是一类常见的符号数据。
Clustering for symbolic data is an important extension of conventional clustering, and interval representation for symbolic data is often used.
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