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1.
This paper presents a new hybrid reliability model which contains randomness, fuzziness and non-probabilistic uncertainty based on the structural fuzzy random reliability and non-probabilistic set-based models. By solving the non-probabilistic set-based reliability problem and analyzing the reliability with fuzziness and randomness, the structural hybrid reliability can be obtained. The presented hybrid model has broad applicability which can handle either linear or non-linear state functions. A comparison among the presented hybrid model, probabilistic and non-probabilistic models, and the conventional probabilistic model is made through two typical numerical examples. The results show that the presented hybrid model, which may ensure structural security, is effective and practical.  相似文献   

2.
The objective of this paper is to critically review the emerging non-probabilistic approaches for uncertainty treatment in finite element analysis. The paper discusses general theoretical and practical aspects of both the interval and fuzzy finite element analysis. First, the applicability of the non-probabilistic concepts for numerical uncertainty analysis is discussed from a theoretical viewpoint. The necessary conditions for a useful application of the non-probabilistic concepts are determined, and are proven to be complementary rather than competitive to the classical probabilistic approach. The second part of the paper focuses on numerical aspects of the interval finite element method. It describes two principal strategies for the implementation, i.e., the anti-optimisation and the interval arithmetic approach, and gives a state-of-the-art of the interval finite element algorithms available from literature. It is shown how the application of the interval arithmetic approach to the classical finite element procedure can result in a severe overestimation of the uncertainty on the output, and the main sources of this conservatism are identified. A numerical example in the final part of the paper illustrates the capabilities of the different strategies on an eigenfrequency analysis of a built-up benchmark structure.  相似文献   

3.
The Minimum Variance Lower Bound (MVLB) represents the best achievable controller capability in a variance sense. Estimation of the MVLB for nonlinear systems confronts some difficulties. If one simply ignores these nonlinearities, there is the danger of over‐estimating the performance of the control loop in rejecting uncertainties. Assuming that almost all models have uncertainties, in this paper, the MVLB has been estimated considering three types of uncertainties: structural, parametric, and algorithmic. To achieve accurate estimation of the MVLB an interval type‐2 fuzzy set has been utilized. This paper utilizes a strategy for modeling of symmetric interval type‐2 fuzzy sets using their uncertainty degrees. Then, based on this uncertainty measure, one method to construct interval type‐2 fuzzy set models using the uncertain interval data is introduced. Finally, simulation studies demonstrate the effectiveness of the proposed control scheme.  相似文献   

4.
The analyses of safety degree and sensitivity for structure are significant in engineering. For the time-dependent structure involving both random and fuzzy inputs, two indices named as the fuzzy time-dependent failure probability and the random time-dependent failure possibility are presented to measure safety degree of time-dependent structure from different aspects, i.e., the fuzzy time-dependent failure probability measures safety degree from the probabilistic view and the random time-dependent failure possibility measures safety degree from the non-probabilistic view. For efficiently estimating these two indices, Genetic Algorithms (GA) is employed. Furthermore, Sparse Grid (SG) technique combined with fourth-moment method is used to estimate the fuzzy time-dependent failure probability. Based on these two safety degree indices, two global sensitivity indices are established. By considering different aspects of the output, the importance ranking of the inputs can be obtained from these two established global sensitivity models. Some efficient procedures are proposed to estimate the global sensitivity indices by combining the three-point estimation method. Several examples containing the numerical and engineering ones are listed to illustrate the effectiveness of the proposed procedures for estimating the two safety degree indices and the two global sensitivity indices.  相似文献   

5.
Management of interval probabilistic data   总被引:1,自引:0,他引:1  
In this paper we present a data model for uncertain data, where uncertainty is represented using interval probabilities. The theory introduced in the paper can be applied to different specific data models, because the entire approach has been developed independently of the kind of manipulated objects, like XML documents, relational tuples, or other data types. As a consequence, our theory can be used to extend existing data models with the management of uncertainty. In particular, the data model we obtain as an application to XML data is the first proposal that combines XML, interval probabilities and a powerful query algebra with selection, projection, and cross product. The cross product operator is not based on assumptions of independence between XML trees from different collections. Being defined with a possible worlds semantics, our operators are proper extensions of their traditional counterparts, and reduce to them when there is no uncertainty. The main practical result of the paper is a set of equivalences that can be used to compare or rewrite algebraic queries on interval probabilistic data, in particular XML and relational.  相似文献   

6.
Processing lineages (also called provenances) over uncertain data consists in tracing the origin of uncertainty based on the process of data production and evolution. In this paper, we focus on the representation and processing of lineages over uncertain data, where we adopt Bayesian network (BN), one of the popular and important probabilistic graphical models (PGMs), as the framework of uncertainty representation and inferences. Starting from the lineage expressed as Boolean formulae for SPJ (Selection–Projection–Join) queries over uncertain data, we propose a method to transform the lineage expression into directed acyclic graphs (DAGs) equivalently. Specifically, we discuss the corresponding probabilistic semantics and properties to guarantee that the graphical model can support effective probabilistic inferences in lineage processing theoretically. Then, we propose the function-based method to compute the conditional probability table (CPT) for each node in the DAG. The BN for representing lineage expressions over uncertain data, called lineage BN and abbreviated as LBN, can be constructed while generally suitable for both safe and unsafe query plans. Therefore, we give the variable-elimination-based algorithm for LBN's exact inferences to obtain the probabilities of query results, called LBN-based query processing. Then, we focus on obtaining the probabilities of inputs or intermediate tuples conditioned on query results, called LBN-based inference query processing, and give the Gibbs-sampling-based algorithm for LBN's approximate inferences. Experimental results show the efficiency and effectiveness of our methods.  相似文献   

7.
Structural reliability is an important method to measure the safety performance of structures under the influence of uncertain factors. Traditional structural reliability analysis methods often convert the limit state function to the polynomial form to measure whether the structure is invalid. The uncertain parameters mainly exist in the form of intervals. This method requires a lot of calculation and is often difficult to achieve efficiently. In order to solve this problem, this paper proposes an interval variable multivariate polynomial algorithm based on Bernstein polynomials and evidence theory to solve the structural reliability problem with cognitive uncertainty. Based on the non-probabilistic reliability index method, the extreme value of the limit state function is obtained using the properties of Bernstein polynomials, thus avoiding the need for a lot of sampling to solve the reliability analysis problem. The method is applied to numerical examples and engineering applications such as experiments, and the results show that the method has higher computational efficiency and accuracy than the traditional linear approximation method, especially for some reliability problems with higher nonlinearity. Moreover, this method can effectively improve the reliability of results and reduce the cost of calculation in practical engineering problems.  相似文献   

8.
Compared with the probability approach, the non-probabilistic convex model only requires a small amount of samples to obtain the variation bounds of the imprecise parameters, and whereby makes the reliability analysis very convenient and economical. In this paper, we attempt to propose and create a correlation analysis technique mathematically for the non-probabilistic convex model, and based on it develop an effective method to construct the multidimensional ellipsoids on the uncertainty. A marginal convex model is defined to describe the variation range of each uncertain parameter, and a covariance is defined to represent the correlation degree of two uncertain parameters. For a multidimensional problem, the covariance matrix and correlation matrix can be created through all marginal convex models and covariances, based on which the required ellipsoid on the uncertainty can be conveniently achieved. By combining the correlation analysis technique and the reliability index approach, a non-probabilistic reliability analysis method is also developed for uncertain structures. Six numerical examples are presented to demonstrate the effectiveness of the present method.  相似文献   

9.
一类非线性离散系统模糊控制器的分析和设计   总被引:1,自引:0,他引:1  
针对一类非线性离散不确定系统,在系统状态不可测的情况下,以T-S模型描述不同状态空间的局部动态区域,并通过中心平均反模糊化、乘积推理、单点模糊化方法得到全局模糊系统模型.基于李亚普诺夫理论和线性矩阵不等式,设计了一种基于观测器的鲁棒控制器,并对离散状态下的此类系统进行了稳定分析.最后通过M ATLAB仿真,证明了该方法的有效性.  相似文献   

10.
利用区间理论并结合求解不确定非线性结构动力学响应的泰勒方法的二阶展开,推导出求解由滞回环本身的不确定性引起的、单自由度不确定滞回系统响应的有效数值方法,得到了系统响应的上下界.并与概率分析方法求得的系统响应进行比较分析,其计算结果与概率方法结果基本相吻合.当求解由滞回环本身的不确定性引起的非线性振动系统的不确定响应问题,而滞回环本身的不确定性统计信息较少概率方法无法适用时,利用本文所推导的区间方法可为工程实际提供参考.  相似文献   

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