可列集合套

[1]中给出模糊集的分解定理与表现定理，指出可利用集合套H＝{H（λ）|λ∈[0,1]}刻化模糊集。本文定义可列集合套H＝{H（a）|a∈Q}，Q是（0，1）的可列稠密子集。相应地给出新的分解定理与表现定理。指出可利用可列集合套刻化的模糊集。     

模糊信息差异及唯一性定理证明

定义了模糊相对熵,基于模糊熵和距离定义了模糊信息差异、拟模糊信息差异,并讨论了模糊信息差异唯一性定理以及模糊信息差异的性质.     

具有多种失效模式的抗震结构的模糊可靠性分析

由于地震荷载和结构抗力具有明显的模糊性,在文献[1,2]中我们提出了具有单一失效模式的抗震结构的模糊可靠性分析.本文将上述概念和方法推广到具有多种失效模式的抗震结构,为此,又提出了结构的“模糊有效域”和“模糊失效域”的概念。     

模糊识别模式在粉土液化判别中的应用

基于模糊数学的基本原理和方法,分析了粉土液化的影响因素,选取粉土的平均粒径,相对密度,标准贯入击数和上覆有效压力作为评价指标,构造粉土液化的模糊识别模式。验证和应用结果表明,模糊识别模式具有很好的映射能力,是粉土液化势预测的有效手段。     

Fuzzy variational principle and its applications

Linear and non-linear peaky fuzzy numbers and their arithmetic operations are constructed for the analysis of engineering structures with fuzzy characteristic quantities. Fuzziness of the corresponding quantities is consistently incorporated into the functional of the total potential energy. A set of deterministic recursive equations is obtained as the alternative expressions of the fuzzy variational principle by means of the second-order perturbation technique. The fuzzy Ritz method and the fuzzy finite element method are presented as the applications of the fuzzy variational principle. Accordingly, the roundabout procedures frequently used in the formulations of the fuzzy finite element method are avoided. A benchmark problem of a bending beam with fuzzy Young's modulus under fuzzy external loading is solved by the developed fuzzy numerical methods. Numerical examples show that results determined by these two fuzzy methods are both little conservative, and are in good agreement with those obtained by the analytical method. Moreover, the fuzzy Ritz method or the fuzzy finite element method can provide more valuable information than the conventional deterministic methods.     

The valuation of life contingencies: A symmetrical triangular fuzzy approximation

This paper extends the framework for the valuation of life insurance policies and annuities by Andrés-Sánchez and González-Vila (2012, 2014) in two ways. First we allow various uncertain magnitudes to be estimated by means of fuzzy numbers. This applies not only to interest rates but also to the amounts to be paid out by the insurance company. Second, the use of symmetrical triangular fuzzy numbers allows us to obtain expressions for the pricing of life contingencies and their variability that are closely linked to standard financial and actuarial mathematics. Moreover, they are relatively straightforward to compute and understand from a standard actuarial point of view.     

Capital allocation for portfolios with non-linear risk aggregation

Existing risk capital allocation methods, such as the Euler rule, work under the explicit assumption that portfolios are formed as linear combinations of random loss/profit variables, with the firm being able to choose the portfolio weights. This assumption is unrealistic in an insurance context, where arbitrary scaling of risks is generally not possible. Here, we model risks as being partially generated by Lévy processes, capturing the non-linear aggregation of risk. The model leads to non-homogeneous fuzzy games, for which the Euler rule is not applicable. For such games, we seek capital allocations that are in the core, that is, do not provide incentives for splitting portfolios. We show that the Euler rule of an auxiliary linearised fuzzy game (non-uniquely) satisfies the core property and, thus, provides a plausible and easily implemented capital allocation. In contrast, the Aumann–Shapley allocation does not generally belong to the core. For the non-homogeneous fuzzy games studied, Tasche’s (1999) criterion of suitability for performance measurement is adapted and it is shown that the proposed allocation method gives appropriate signals for improving the portfolio underwriting profit.     

Fuzzy logic modifications of the Analytic Hierarchy Process

The Analytic Hierarchy Process (AHP) is a measurement methodology based on pair-wise comparisons that relies on judgment to derive priority scales. During its implementation, one constructs hierarchies, then makes judgments or performs measurements on pairs of elements with respect to a criterion to derive preference scales, which are then synthesized throughout the structure to select the preferred alternative.One of the areas where the AHP finds application is in the subjective phases of risk assessment (RA), where it is used to structure and prioritize diverse risk factors, including the judgments of experts. Since fuzzy logic (FL) has been shown to be an effective tool for accommodating human experts and their communication of linguistic variables, there has been research aimed at modeling the fuzziness in the AHP (FAHP), and recently the focus of some of that modeling has been with respect to RA.The literature discusses more than one FAHP model, which raises the question as to which are the prominent models and what are their characteristics. In response to this question, we examine three of the most influential FAHP models. The article proceeds as follows. It begins with a brief overview of the AHP and its limitations when confronted with a fuzzy environment. This is followed by a discussion of FL modifications of the AHP. A RA-based likelihood score example is used throughout. The article ends with a commentary on the findings.     

1H NMR and UV-visible data fusion for determining Sudan dyes in culinary spices

Two data fusion strategies (variable and decision level) combined with a multivariate classification approach (Partial Least Squares-Discriminant Analysis, PLS-DA) have been applied to get benefits from the synergistic effect of the information obtained from two spectroscopic techniques: UV-visible and ¹H NMR. Variable level data fusion consists of merging the spectra obtained from each spectroscopic technique in what is called “meta-spectrum” and then applying the classification technique. Decision level data fusion combines the results of individually applying the classification technique in each spectroscopic technique. Among the possible ways of combinations, we have used the fuzzy aggregation connective operators. This procedure has been applied to determine banned dyes (Sudan III and IV) in culinary spices. The results show that data fusion is an effective strategy since the classification results are better than the individual ones: between 80 and 100% for the individual techniques and between 97 and 100% with the two fusion strategies.