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当模糊变量的隶属函数为正态型时,可以将模糊随机可靠性及可靠性灵敏度转化为随机可靠性及可靠性灵敏度,并利用复合函数求导法则求解模糊随机失效概率对正态型隶属函数分布参数的灵敏度.对于对称抛物型隶属函数,文中提出了"改进最大最小"法和"改进等面积"法两种近似等价正态化方法,从而将模糊随机可靠性问题转换为随机可靠性问题,并利用线抽样方法分析之.算例结果表明,由于"改进最大最小"法所得的等价正态型隶属函数能在函数图形尾部更好地近似对称抛物型隶属函数,因而"改进最大最小"法更适用于模糊变量的隶属函数为对称抛物型分布时模糊随机可靠性及可靠性灵敏度的近似计算. 相似文献
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本文以适当方式构造满足模糊约束条件的各模糊目标集的隶属函数;基于模糊判决原理,兼顾模糊目标和模糊约束的最优性隶属程度,构造判决函数;对多目标结构模糊优化设计提出了四种方法:最大最小法,理想点法,线性加权法和功效系数法;最终均化成普通单目标数学规划求解;并以两个实例加以说明。 相似文献
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基于模糊事件概率理论的模糊可靠性分析通用方法 总被引:5,自引:0,他引:5
讨论了从已知的模糊信息的隶属函数,确定模糊失效事件的隶属函数的方法,以便能利用模糊事件概率理论进行模糊可靠性分析,给出模糊可靠性分析通用而统一的方法;并给出了强度为几种常用模糊分布时,所确定的模糊失效事件的隶属函数的具体表达式,分析了模糊失效事件的隶属函数的曲线特性。由于获得的模糊失效事件的隶属函数的形式比较复杂,用模糊事件概率理论进行模糊可靠性分析时,不可能得到计算模糊失效事件概率的解析式,因此通过仿真所确定的模糊失效事件的隶属函数的数学期望的方法,估计模糊失效事件的发生概率。本文讨论的通过确定模糊事件的隶属函数,用模糊事件概率理论进行模糊可靠性分析的方法具有普遍意义。 相似文献
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动态设计变量优化方法及其在工程静力学通用程序设计中的应用 总被引:5,自引:0,他引:5
本文提出动态设计变量优化新方法并解决理论和工程问题,该方法首先构建目标函数框架,然后根据具体问题的输入条件,动态地进行设计变量分配和合理排序,形成实际问题的动态目标函数。基于动态设计变量优化方法,编制出一个能解决单刚体、刚体系的平面和空间问题、摩擦问题和桁架所有工程静力学平衡问题的通用程序,并通过实例分析验证。为解决更多工程领域问题提供有效新观点。 相似文献
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模糊随机可靠性分析的统一模型 总被引:13,自引:1,他引:13
针对基本变量和状态变量的不确定性可能既有随机性又有模糊性的情况,通过
引入规一化因子和模糊变量隶属函数的等效概率密度函数转换,建立了同时考虑随机和模糊
两种不确定性因素的统一可靠性模型. 由于该模型将模糊变量等价转换成了随机变量,并且
这种等价变换没有改变模糊变量的可能性分布,因而随机可靠性模型的所有方法均可用于统
一模型,并且其可靠度和失效概率的计算将是准确的. 所提模型不仅适用于只有应力和强度
两个基本变量的情况,而且也适用于多个变量的情况. 用算例对所提模型与前人的采
用截集并在截集中引入人为分布的模型进行了对比,结果表明该方法更适于工程应用. 相似文献
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基于混合行为博弈的多目标仿生设计方法 总被引:2,自引:0,他引:2
将多个设计目标视为不同的博弈方,通过计算设计变量对目标函数的影响因子和模糊聚类,
将设计变量集合分割为各博弈方拥有的策略空间. 对蜥蜴种群的繁衍生存机理进行仿生,将
3种蜥蜴的行为方式分别定义为利己主义、集体主义和投机主义,并赋予相应的博弈方,
各博弈方根据所仿生蜥蜴的行为特点,建立自身博弈得益函数与目标函数之间的映射关系.
各博弈方分别以自身博弈得益函数为目标,在各自的策略空间中进行单目标优化,获得本博
弈方对其余博弈方的最佳对策,所有博弈方的最佳对策形成一轮博弈的策略组合,并根据收
敛判别,通过多轮博弈,获得最终的博弈解. 以白鹤滩拱坝体型的三目标优化设计为例,设
计结果显示坝体体积方量减少了16.412万方,或2.38%; 最大主拉应力降低
了0.036MPa, 或0.31%; 整体应变能下降了0.167GJ 或4.47% 体现了基
于混合行为博弈方式的多目标仿生设计方法的有效性. 相似文献
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设计标准中对构件适用功能的要求常具有一定的模糊性,结构可靠度分析中应考虑这种不确定性的影响。目前虽然利用模糊集合及其隶属函数,建立了功能要求模糊时构件可靠度的分析方法,但它们在作用概率组合、功能函数表达、模糊概率计算等方面仍存在一定的不足。为此,首先在作用概率组合中引入更为合理的随机过程组合方法,并采用便于反映设计中各种情况的量纲为一形式的功能函数;其次,重点针对适用功能要求的模糊性,通过引入模糊边界,提出概念更为明晰的模糊概率简化计算方法,最终形成完整的功能要求模糊时构件可靠度分析的基本方法。该方法具有更为合理的理论基础和更好的精度,且便于应用。 相似文献
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The key component of finite element analysis of structures with fuzzy parameters, which is associated with handling of some fuzzy information and arithmetic relation of fuzzy variables , was the solving of the governing equations of fuzzy finite element method. Based on a given interval representation of fuzzy numbers, some arithmetic rules of fuzzy numbers and fuzzy variables were developed in terms of the properties of interval arithmetic. According to the rules and by the theory of interval finite element method, procedures for solving the static governing equations of fuzzy finite element method of structures were presented. By the proposed procedure, the possibility distributions of responses of fuzzy structures can be generated in terms of the membership functions of the input fuzzy numbers. It is shown by a numerical example that the computational burden of the presented procedures is low and easy to implement. The effectiveness and usefulness of the presented procedures are also illustrated. 相似文献
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Fuzzy reliability analysis can be implemented using two discrete optimization maps in the processes of reliability and fuzzy analysis. Actually, the efficiency and robustness of the iterative reliability methods are two main factors in the fuzzy-based reliability analysis due to the huge computational burdens and unstable results. In the structural fuzzy reliability analysis, the first-order reliability method (FORM) using discrete nonlinear map can provide a C membership function. In this paper, a discrete nonlinear conjugate map is proposed using a relaxed-finite step size method for fuzzy structural reliability analysis, namely Fuzzy conjugate relaxed-finite step size method fuzzy CRS. A discrete conjugate map is stabilized using two adaptive factors to compute the relaxed factor and step size in FORM. The framework of the proposed fuzzy structural reliability method is established using two linked iterative discrete maps as an outer loop, which constructs the membership function of the response using alpha level set optimization based on genetic operator, and the inner loop, implemented for reliability analysis using proposed conjugate relaxed-finite step size method. The fuzzy CRS and fuzzy HL-RF methods are compared to evaluate the membership functions of five structural problems with highly nonlinear limit state functions. Results demonstrated that the fuzzy CRS method is computationally more efficient and is strongly more robust than the HL-RF for fuzzy-based reliability analysis of the nonlinear structural reliability problems. 相似文献
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Kuo-Kai Shyu Thi-Thao Tran Van-Truong Pham Po-Lei Lee Li-Jen Shang 《Nonlinear dynamics》2012,69(1-2):295-312
This paper presents an unsupervised fuzzy energy-based active contour model for image segmentation, based on techniques of curve evolution. The paper proposes a fuzzy energy functional which involves intensity distributions in regions of image to segment and value of fuzzy membership functions. The intensity distributions are derived using a Gaussian mixture model (GMM)-based intensity distribution estimator. Meanwhile, the fuzzy membership functions valued in [0,1] is used to measure the association degree of each image pixel to the region outside and inside the curve. The proposed energy functional is then incorporated into a pseudo-level set formulation. To minimize the energy functional, instead of solving Euler?CLagrange equation of underlying problem, we utilize a direct method to calculate the alterations of the fuzzy energy. In addition, since the parameters of intensity distributions are preestimated, the proposed model avoids the step of updating them at each iteration of curve evolution. The proposed model therefore overcomes the initialization problem of common gradient-descent-based active contour models and converges quickly. Besides, it can work with images with blurred object boundaries. In addition, the extension of the model for the more general case of local space-varying intensities enables dealing with images with intensity inhomogeneity. Experimental results for synthetic and real images validate the desired performances of the proposed model. 相似文献
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边坡稳定性预测的模糊神经网络模型 总被引:1,自引:0,他引:1
根据边坡稳定问题具有的模糊性,提出了一种判定边坡稳定性的模糊神经网络模型。该系统仅从期望输入输出数据集即可达到获取知识、确定模糊初始规则基的目的。再利用神经网络学习能力便不难修改规则库中的模糊规则以及隶属函数和网络权值等参数,这样大大减少了规则匹配过程,加快了推理速度,从而极大程度地提高了系统的自适应能力。最后用收集到的边坡数据样本训练和测试模糊神经网络模型,结果表明该模糊神经网络预测边坡稳定性是可行的、有效的。 相似文献