改进的简化决策表及属性约简

研究了不一致决策表的简化与属性约简问题,指出目前简化的决策表的局限:在简化的决策表上用现有的属性约简方法与在原决策表上基于正区域的属性约简方法,所得到的结果不一致.进一步对简化的决策表进行转换,得到新的决策表.基于正区域的属性约简,证明了在原决策表上约简与在新的决策表上约简结果相同.从而保证在实际应用中,对新的决策表可以用任意一种属性约简方法.     

优势关系下决策表的下近似约简方法研究

研究了优势关系下不协调决策表的下近似约简问题,引入新的下近似约简的定义,证明新的下近似约简与文献[7]定义的下近似约简等价。给出新的下近似约简的判定定理和辨识矩阵,与文献[7]的辨识矩阵相比,计算新的下近似约简的辨识矩阵的时间复杂度要低。因此,可以利用新的辨识矩阵来求决策表的下近似约简．     

多集值信息表中的多粒度模糊决策论粗糙集

多粒度粗糙集和决策论粗糙集是Pawlak粗糙集的重要推广,目前已成为人工智能研究的热点.然而,它们大多处理的都是单值信息系统中的问题.而实际生活中绝大多数都是处理多值问题,为了解决这一问题,在多集值信息表中将多粒粗糙集与模糊决策论粗糙集相结合进行研究,提出了其在乐观,悲观情形下的上下近似,研究了一些相关性质并给出了多集值信息表中的多粒度模糊决策论粗糙集精度、粗度的概念,最后通过一个具体例子验证其有效性.     

协调决策理论及其智能化决策支持系统

本文针对多因素决策问题 ,建立了一种多专家协调决策的理论、方法、计算过程和应用实例 .设计了相应的智能化计算机决策支持系统 .     

Dominance-based fuzzy rough set analysis of uncertain and possibilistic data tables

In this paper, we propose a dominance-based fuzzy rough set approach for the decision analysis of a preference-ordered uncertain or possibilistic data table, which is comprised of a finite set of objects described by a finite set of criteria. The domains of the criteria may have ordinal properties that express preference scales. In the proposed approach, we first compute the degree of dominance between any two objects based on their imprecise evaluations with respect to each criterion. This results in a valued dominance relation on the universe. Then, we define the degree of adherence to the dominance principle by every pair of objects and the degree of consistency of each object. The consistency degrees of all objects are aggregated to derive the quality of the classification, which we use to define the reducts of a data table. In addition, the upward and downward unions of decision classes are fuzzy subsets of the universe. Thus, the lower and upper approximations of the decision classes based on the valued dominance relation are fuzzy rough sets. By using the lower approximations of the decision classes, we can derive two types of decision rules that can be applied to new decision cases.     

Highly accurate tables for elementary functions

In this article we describe a fast method to obtain highly accurate tables for all elementary functions by using Bresenham's algorithm. For nearly equally spaced table-points {x _i } we construct pairs {f(x _i ),g(x _i )} such thatf(x _i ) is a machine number andg(x _i ) is very close to an exactly representable number. By a random sampling in an interval centered onx _i we can even find a triplet of nearly machine numbers. The table method together with a polynomial approximation of the function near a table value provides last bit accuracy for more than 99.8% of the argument values without using extended precision calculations [3, 4, 10, 11].     

物元评判模型及其在教学评估中的应用

对物元评判模型的建模方法进行了分析,将它应用到教学质量的评定中,分析表明它为一类优良模型,能有效应用于教学评估中.     

聚类分析的竞争决策算法

聚类分析是数据挖掘的重要技术,是一种无监督的学习方式,可根据数据间的相似程度,将数据进行分类.竞争决策算法是一种基于竞争造就优化和决策左右结果的新型优化算法,针对聚类分析的特点,设计了一种竞争决策算法进行求解,经实验测试和验证,并与其它算法的结果进行比较,获得了较好的结果.     

不确定性量化法与不确定性决策

以不确定性信息的数学处理理论即不确定性数学理论为基础 ,阐述了专家意见的不确定性量化法 ,进而创立了不确定性决策模型 .最后通过举例 ,详细地演示了不确定性决策模型的建立过程 .     

模糊决策分析在电子政务中的应用

电子政务系统中,信息量庞大.主要讨论了模糊决策分析理论在电子政务中的应用.分析了在实际应用过程中,不同参数的取值,对数据产生怎样的影响,以及如何对人才的取舍作出决策.     

一种基于决策矩阵的DST-AHP多属性决策方法

针对层次分析法决策时存在两两判断、一致性检验次数过多和判断矩阵残缺性等问题,本文提出了一种基于决策矩阵的DST-AHP多属性决策方法。该方法结合决策矩阵的特征值,构建DST-AHP方法层次结构模型和判断矩阵,并根据判断矩阵定义不同属性下各焦元的基本概率分配函数;然后利用Dempster合成法则对基本概率分配函数值进行合成,依据合成后值对方案进行排序。最后对AHP和DST-AHP两种方法进行比较分析,说明该方法的有效性。     

基于熵的多目标多维模糊决策模型

顾及多目标多维决策中存在的模糊性和随机性,基于Jaynes的信息熵最大原理,提出一种模糊环境下带有主观监督因子和信息熵的目标函数,导出了新的计算模糊决策识别矩阵与目标权重的模糊交叉计算公式.该模型将基于目标的客观决策与主观决策有机结合起来,为求解最优模糊决策识别矩阵和确定目标最优权重提供了一种有效途径,并把信息熵作为评价决策优劣的指标,进一步发展了多目标多维模糊决策理论模型.将本文提出的模糊决策方法应用于16家电炉炼钢企业的模糊综合评价,取得了较为满意的效果.     

基于最小错误率贝叶斯决策的企业员工招聘决策

本在[1]和[2]研究基础上，利用[1]、[2]中的分析模型和综合评价模型所得的结果。以及这两个结果正相关性。依据某大型国有企管理初级岗位3000多人的测试结果。采用最小错误率贝叶斯决策。构建了企业管理岗位初级人员招聘模型。此模型为企业根据企业化和价值观等来招聘符合企业要求的员工提供了一种方法。     

决策方法在反问题研究中的应用

本文讨论了决策方法在反问题研究中的应用.首先阐述在反问题研究中应用决策方法的必要性,然后以一个具体的反问题为例论述了如何确立决策目标.     

动态逆在投资决策中的应用

本文利用动态逆给出了为达到计划期末年产值X(m)，计划期内各年度应达到的增长量△X（t）的测算方法，为实现增长量△X（t）所必要的投资额的测算方法，并且进一步给出计划期内第t年全社会（区域）的投资总量以及计划期内全社会（区域）的投资累计总量等计算公式。     

层次分析法在选股决策中的应用

应用层次分析法建立了股票选择的数学模型,并选择了4只热门股票作为备选股票,从理论和实际两方面对模型的合理性进行了检验.     

Quasi-diagonal exponent symmetry model for square contingency tables with ordered categories

For square contingency tables, we propose a quasi-symmetry model with an exponential form along subdiagonal and give the theorem that Tomizawa’s (1992) diagonal exponent symmetry model holds if and only if the proposed model and marginal means equality model hold with the orthogonality of test statistics.     

Efficient visit frequencies for polling tables: minimization of waiting cost

Polling systems have been used as a central model for the modeling and analysis of many communication systems. Examples include the Token Ring network and a communications switch. The common property of these systems is the need to efficiently share a single resource (server) amongN entities (stations). In spite of the massive research effort in this area, very little work has been devoted to the issue of how toefficiently operate these systems.In the present paper we deal with this problem, namely with how to efficiently allocate the server's attention among theN stations. We consider a framework in which a predetermined fixed visit order (polling table) is used to establish the order by which the server visits the stations, and we address the problem of how to construct an efficient (optimal) polling table. In selecting a polling table the objective is to minimize the mean waiting cost of the system, a weighted sum of the mean delays with arbitrary cost parameters. Since the optimization problem involved is very hard, we use an approximate approach. Using two independent analyses, based on a lower bound and on mean delay approximations, we derive very simple rules for the determination of efficient polling tables. The two rules are very similar and even coincide in most cases. Extensive numerical examination shows that the rules perform well and that in most cases the system operates very close to its optimal operation point.     

未确知数学在决策中的应用

以不确定性信息处理的数学理论为基础,分析某欲建水库方案是否可行为例,说明了未确知数学在决策中的应用,同时本文还给出了未确知决策的一般公式.     

群体决策中专家联盟的影响指数的研究

运用Shapley定量，解决专家在不一致时的影响指数问题，从而为专家谈判时的个人贡献以及影响问题提供依据，使层次分析中专家矩阵的可信性提高，供决策更好地决策，最后用算例说明。