基于Mamdani型模糊推理的震中烈度预测模型

对应用模糊推理进行系统预测进行了深入的研究,建立了以震级和震源深度为输入的基于Mamdani型模糊推理的震中烈度预测模型.并以四川地区震例数据为例,对数据信息提取,模糊规则建立等关键环节进行了详细的介绍,预测结果分析表明推理模型是可行和有效的.     

Parameter Estimation of Multivariate Regression Model with Fuzzy Random Errors

In many real-world problems, observations are usually described by approximate values due to fuzzy uncertainty, unlikeprobabilistic uncertainty that has nothing to do with experimentation. The combination of statistical model and fuzzy set theory is helpful to improve the identification and analysis of complex systems. As an extension ofstatistical techniques, this study is an investigation of the relationship between fuzzy multiple explanatory variables and fuzzy response with numeric coefficients and the fuzzy random error term. In this work we describe a parameter estimation procedure carrying out the least-squares method in a complete metric space of fuzzy numbers to determine the coefficients based on the extension principle. We demonstrate how the fuzzy least squares estimators present large sample statistical properties, including asymptotic normality, strong consistency and confidence region. The estimators are also examined via asymptotic relative efficiency concerning traditional least squares estimators. Different from the construction of error term in Kim et al.\cite{21}, it is more reasonable in the proposed model since the problems of inconsistency in referring to fuzzy variable and producing the negative spreads may be avoided. The experimental study verifies that the proposed fuzzy least squares estimators achieve the meaning consistent with the theory identification for large sample data set and better generalization regarding one single variable model.     

Markov-modulated Hawkes process with stepwise decay

This paper proposes a new model—the Markov-modulated Hawkes process with stepwise decay (MMHPSD)—to investigate the variation in seismicity rate during a series of earthquake sequences including multiple main shocks. The MMHPSD is a self-exciting process which switches among different states, in each of which the process has distinguishable background seismicity and decay rates. Parameter estimation is developed via the expectation maximization algorithm. The model is applied to data from the Landers–Hector Mine earthquake sequence, demonstrating that it is useful for modelling changes in the temporal patterns of seismicity. The states in the model can capture the behavior of main shocks, large aftershocks, secondary aftershocks, and a period of quiescence with different background rates and decay rates.     

多重模糊蕴涵与生成模糊蕴涵的新方法

提出一种生成模糊蕴涵的新方法,即通过一个或多个选定的模糊蕴涵作多重迭代生成新的模糊蕴涵,称为多重模糊蕴涵.从选定的模糊蕴涵出发,根据不同的迭代次数,分别证明迭代结果仍为模糊蕴涵.进一步,分析当选定的模糊蕴涵具有某种性质时,所生成的多重模糊蕴涵是否仍保持这些性质.还对选定的模糊蕴涵分别为(S,N)-蕴涵和R-蕴涵这两种重要情形,进行更深入的分析.这些结果将为模糊蕴涵在控制及决策等领域的应用提供支持.     

三角模糊数直觉模糊PA算子及其应用

针对决策信息为三角模糊数直觉模糊数（TFNIFN）且属性间存在相互关联的多属性群决策（MAGDM）问题,提出了一种基于三角模糊数直觉模糊PA （TFNIFPA）算子的决策方法.首先,基于TFNIFN的运算法则和PA （Power Average）算子,定义了TFNIFPA算子.然后,研究了该算子的一些性质,建立基于TFNIFPA算子的MAGDM模型,结合排序方法进行决策.最后通过MAGDM算例验证了该算子的有效性与可行性.     

基于时间度的动态直觉模糊多属性妥协决策

针对当前动态直觉模糊多属性决策方法存在的不足,提出一种基于时间度的动态直觉模糊妥协决策方法。引入时间度准则,基于逼近理想解法融合主客观两类赋权法,获得兼顾主观偏好和样本客观信息的时序权重,克服现有时序权重主观赋值的随意性,同时运用直觉模糊熵(IFE)确定不同时序状态下各属性权重;根据动态直觉模糊加权几何算子(DIFWG)集结不同时序直觉模糊决策矩阵,构造动态直觉模糊综合决策矩阵,并利用VIKOR法,提供兼顾群体效用最大化与个体后悔最小化的各方案妥协折中排序,得到与理想解最近的妥协方案;以分布式创新企业合作伙伴选择为例,验证该方法在实际决策过程中的可行性和有效性。     

Intuitionistic and interval-valued intutionistic fuzzy preference relations and their measures of similarity for the evaluation of agreement within a group

Szmidt and Kacprzyk (Lecture Notes in Artificial Intelligence 3070:388–393, 2004a) introduced a similarity measure, which takes into account not only a pure distance between intuitionistic fuzzy sets but also examines if the compared values are more similar or more dissimilar to each other. By analyzing this similarity measure, we find it somewhat inconvenient in some cases, and thus we develop a new similarity measure between intuitionistic fuzzy sets. Then we apply the developed similarity measure for consensus analysis in group decision making based on intuitionistic fuzzy preference relations, and finally further extend it to the interval-valued intuitionistic fuzzy set theory.     

Triple I method of approximate reasoning on Atanassov's intuitionistic fuzzy sets

Two basic inference models of fuzzy reasoning are fuzzy modus ponens (FMP) and fuzzy modus tollens (FMT). The Triple I method is a very important method to solve the problems of FMP and FMT. The aim of this paper is to extend the Triple I method of approximate reasoning on Atanassov's intuitionistic fuzzy sets. In the paper, we first investigate the algebra operators' properties on the lattice structure of intuitionistic fuzzy information and provide the unified form of residual implications which indicates the relationship between intuitionistic fuzzy implications and fuzzy implications. Then we present the intuitionistic fuzzy reasoning version of the Triple I principles based on the models of intuitionistic fuzzy modus ponens (IFMP) and intuitionistic fuzzy modus tollens (IFMT) and give the Triple I method of intuitionistic fuzzy reasoning for residual implications. Moreover, we discuss the reductivity of the Triple I methods for IFMP and IFMT. Finally, we propose α-Triple I method of intuitionistic fuzzy reasoning.     

基于Hausdauff度量的模糊TOPSIS方法研究

针对模糊多属性决策中的模糊 TOPSIS方法 ,提出了一种基于 Hausdauff度量的模糊 TOPSIS方法 .首先由模糊极大集与模糊极小集确定模糊多属性决策问题的理想解与负理想解 ,进而由 Hausdauff度量获得不同备选方案到理想解与负理想解的距离及其贴近度 ,根据贴近度指标对方案进行排序 ,为决策者提供决策支持 .最后以 L-R梯形模糊数为例进行了实例研究 .     

直觉模糊数的序优先度及其在群评价中的应用

直觉模糊数是处理模糊问题的一种有效的信息表达形式,其排序方法是研究的热点问题之一.基于均匀分布的原理,提出新的直觉模糊数序优先度的概念,给出各种情形下的序优先度的计算公式,并探讨了直觉模糊数序优先度的若干性质.给出了基于直觉模糊数序优先度的群评价算法.实例分析表明本文提出的方法是可行有效的.