一种基于Fuzzy数学的计算机故障诊断新方法

提出了一种新的模糊诊断方法,建立了故障诊断的数学模型,并在计算机上实现了模糊诊断的仿真实验,并通过实例说明了这种方法有利于提高决策的准确性和可信度,在实际应用中是有效和可行的.     

模糊综合评判法在创业机会评估中的应用研究

创业是极具风险的活动.在我国,创业企业的失败率是非常高的.创业机会稍纵即失,正确评价和把握创业机会,这对创业者和创业资本的提供者都十分重要.在Timmons的创业机会评价框架下,提出了创业机会综合评价的指标体系,建立了创业机会模糊综合评价模型,并给出算法,最后进行了实证分析.     

��Ⱦ��������ض�������ģ�͵IJ�������

本文研究了线性模型响应变量被污染且被区间截断下的参数估计问题, 借助于区间数据的无偏转换, 得到了回归系数和污染系数的估计, 并在一定的条件下得到了这些估计的强相合性. 通过若干模拟例子说明, 尽管数据经过污染和区间截断的双重信息损失, 但用本文提出的方法得到的估计, 仍能取得良好的估计效果     

新建住房套型比例的合理性研究

本文以建设部提出的新建住房套型比例合理性为研究对象。基于我国城镇居民的年人均可支配收入的分布情况,依据《中国统计年鉴》的数据,用F分布拟合变换后年人均可支配收入,得年人均可支配收入密度函数;运用广义最小二乘估计人均年可支配收入与人均年最大可用于购房支出的线性关系;综合考虑人均可支配收入、家庭人口数的分布,首付率、按揭贷款年限、年利率和新建住房交易价对购房面积的影响,得家庭意向购房面积分布函数和合理的套型建筑面积结构比例。     

基于格半群的有限状态自动机的同态

本文研究了格值有限状态自动机(LFSA)的同态和强同态及其性质.利用强同态概念,在格值有限状态自动机的状态集上建立了一种等价关系,得到了格值有限状态自动机的商自动机,证明了商自动机与强同态像自动机同构.     

An adaptive network based fuzzy inference system–auto regression–analysis of variance algorithm for improvement of oil consumption estimation and policy making: The cases of Canada,United Kingdom,and South Korea

This paper presents an adaptive network based fuzzy inference system (ANFIS)–auto regression (AR)–analysis of variance (ANOVA) algorithm to improve oil consumption estimation and policy making. ANFIS algorithm is developed by different data preprocessing methods and the efficiency of ANFIS is examined against auto regression (AR) in Canada, United Kingdom and South Korea. For this purpose, mean absolute percentage error (MAPE) is used to show the efficiency of ANFIS. The algorithm for calculating ANFIS performance is based on its closed and open simulation abilities. Moreover, it is concluded that ANFIS provides better results than AR in Canada, United Kingdom and South Korea. This is unlike previous expectations that auto regression always provides better estimation for oil consumption estimation. In addition, ANOVA is used to identify policy making strategies with respect to oil consumption. This is the first study that introduces an integrated ANFIS–AR–ANOVA algorithm with preprocessing and post processing modules for improvement of oil consumption estimation in industrialized countries.     

Extension of the TOPSIS method for decision making problems under interval-valued intuitionistic fuzzy environment

TOPSIS is one of the well-known methods for multiple attribute decision making (MADM). In this paper, we extend the TOPSIS method to solve multiple attribute group decision making (MAGDM) problems in interval-valued intuitionistic fuzzy environment in which all the preference information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFNs), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and construct the weighted collective interval-valued intuitionistic fuzzy decision matrix, and then determine the interval-valued intuitionistic positive-ideal solution and interval-valued intuitionistic negative-ideal solution. Based on different distance definitions, we calculate the relative closeness of each alternative to the interval-valued intuitionistic positive-ideal solution and rank the alternatives according to the relative closeness to the interval-valued intuitionistic positive-ideal solution and select the most desirable one(s). Finally, an example is used to illustrate the applicability of the proposed approach.     

知识型员工行为能力的构成要素与评价研究

行为能力对于解释员工绩效具有重要意义.本文以知识型员工为研究对象,通过规范的实证研究获得了知识型员工行为能力的构成要素,以此为基础构建了知识型员工行为能力的评价指标体系.根据指标模糊性的特点,将三角模糊数理论与FAHP的融合,提出了一种基于三角模糊数的FAHP评价方法.以DR公司招聘某岗位的知识型员工为实例,说明了本文提出的方法在知识型员工行为能力评价中的适用性.     

一种基于组合不确定型OWA算子的区间数群决策方法

在群决策中,由于决策环境的不确定性,决策者给出区间效信息.基于区间数可能度矩阵公式和互补判断矩阵的排序公式,提出了一种组合不确定型OWA算子,它是不确定型OWA算子的推广.该算子能集结群决策中区间数信息,文中给出了其在应用的具体步骤,最后实例分析说明了该方法的有效性和可行性.     

均匀分布参数的无偏估计及其分布

讨论了均匀分布未知参数无偏估计量的分布密度,利用无偏估计量构造出一些新的样本函数,并且利用给出的样本函数推导出了未知参数的置信区间.所得到结果改善了现有的估计,易于计算.