Performance evaluation of nonlinear optimization methods via pairwise comparison and fuzzy numbers

In this paper we extend the deterministic performance evaluation of nonlinear optimization methods: we carry out a pairwise comparison using fuzzy estimates of the performance ratios to obtain fuzzy final scores of the methods under consideration. The key instrument is the concept of fuzzy numbers with triangular membership functions. The algebraic operations on them are simple extensions of the operations on real numbers; they are exact in the parameters (lower, modal, and upper values), not necessarily exact in the shape of the membership function. We illustrate the fuzzy performance evaluation by the ranking and rating of five methods (geometric programming and four general methods) for solving geometric-programming problems, using the results of recent computational studies. Some general methods appear to be leading, an outcome which is not only due to their performance under subjective criteria like domain of applications and conceptual simplicity of use; they also score higher under more objective criteria like robustness and efficiency.     

具有Fuzzy概率的Fuzzy可靠性问题的求解途径

本文提出了工程实践中常见的清晰事件－Ｆｕｚｚｙ概率的Ｆｕｚｚｙ可靠性分析问题的求解途径，首先讨论了Ｆｕｚｚｙ数的代数运算法则，然后在此基础上将Ｆｕｚｚｙ可靠性求解问题转换为Ｆｕｚｚｙ数的运算问题，从而使这类Ｆｕｚｚｙ可靠性分析问题在理论上得到解决，本文还给出了一个算例。     

Fuzzy sets and type 2 under algebraic product and algebraic sum

The concept of fuzzy sets of type 2 has been proposed by L.A. Zadeh as an extension of ordinary fuzzy sets. A fuzzy set of type 2 can be defined by a fuzzy membership function, the grade (or fuzzy grade) of which is taken to be a fuzzy set in the unit interval [0, 1] rather than a point in [0, 1].This paper investigates the algebraic properties of fuzzy grades (that is, fuzzy sets of type 2) under the operations of algebraic product and algebraic sum which can be defined by using the concept of the extension principle and shows that fuzzy grades under these operations do not form such algebraic structures as a lattice and a semiring. Moreover, the properties of fuzzy grades are also discussed in the case where algebraic product and algebraic sum are combined with the well-known operations of join and meet for fuzzy grades and it is shown that normal convex fuzzy grades form a lattice ordered semigroup under join, meet and algebraic product.     

ETSK模糊模型辨识及模糊控制算法

本文提出一种基于扩张原理的ＥＴＳＫ（ＥｘｔｅｎｄｅｄＴＳＫ）模型,导出了该模型的输入输出解析式,给出了辨识这种模型的方法。本文还导出了ＥＴＳＫ模型的一种等价形式——变权ＴＳＫ模型,从而将ＥＴＳＫ模型规则后件中的模糊数及其扩展运算转化为普通数的运算,使基于ＥＴＳＫ模型的模糊控制算法ＭＢＦＣ（Ｍｏｄｅｌ－ＢａｓｅｄＦｕｚｚｙＣｏｎｔｒｏｌ）易于实现。仿真辨识结果表明,ＥＴＳＫ模型的辨识效果和预报精度优于ＴＳＫ和ＬＭ模型;ＭＢＦＣ算法的控制效果优于通常模型ＰＩ控制算法     

Algebraic properties of complex fuzzy events in classical and in quantum information systems

Baer¹-semigroups are regarded as the main abstract structures for an algebraic analysis of complex fuzzy events in generalized probability theory. This assumption is verified in the case of classical probability theory in the framework of measure and integration theory. The corresponding fuzzy language is extended to the non-commutative probability theory based on operators in Hilbert space.Starting from a quantum information system a quantum probability space is constructed, which is naturally embedded in a classical information system. In this last both exact than fuzzy quantum events are represented as classical fuzzy events. Lastly, the classical fuzzy events which correspond to exact quantum events are characterized by some minimality properties.     

An Efficient Algorithm for Generating Univariate Cubic L 1 Splines

An active set based algorithm for calculating the coefficients of univariate cubic L ₁ splines is developed. It decomposes the original problem in a geometric-programming setting into independent optimization problems of smaller sizes. This algorithm requires only simple algebraic operations to obtain an exact optimal solution in a finite number of iterations. In stability and computational efficiency, the algorithm outperforms a currently widely used discretization-based primal affine algorithm.     

Fuzzy real algebra: Some results

In this paper, the possibility to perform easily most of the extended n-ary operations on fuzzy subsets of the real line is shown. A general algorithm is given. These results are particularized for usual operations such as addition, subtraction, multiplication, division, ‘max’ and ‘min’ operations for normalized convex fuzzy subsets of the real line, i.e. fuzzy numbers. A three parameters representation for fuzzy numbers is shown to be very convenient to perform usual operations. Lastly, interpretative comments about fuzzy real algebra are given and possible applications pointed out.     

Extension principles for interval-valued intuitionistic fuzzy sets and algebraic operations

The Atanassov’s intuitionistic fuzzy (IF) set theory has become a popular topic of investigation in the fuzzy set community. However, there is less investigation on the representation of level sets and extension principles for interval-valued intuitionistic fuzzy (IVIF) sets as well as algebraic operations. In this paper, firstly the representation theorem of IVIF sets is proposed by using the concept of level sets. Then, the extension principles of IVIF sets are developed based on the representation theorem. Finally, the addition, subtraction, multiplication and division operations over IVIF sets are defined based on the extension principle. The representation theorem and extension principles as well as algebraic operations form an important part of Atanassov’s IF set theory.     

精确解析法的子结构算法

文[1]提出精确解析法,用以求解任意变系数常微分方程,并利用初参数算法给出一个解的解析表达式.但利用初参数算法,对某一类问题,如长柱壳弯曲和振动等,它们的解将难以在计算机上得到.本文通过非均匀轴对称长圆柱壳弯曲问题,给出精确解析法的子结构算法,它能够计算初参数算法在计算机上不能解决的问题.问题最后和初参数算法一样能归结为求解一个低阶代数方程组.文末给出算例,表明本文算法的正确性,并和初参数算法作了比较.     

Sparse approximate solutions to stochastic Galerkin equations

In this Note, we formulate a sparse Krylov-based algorithm for solving large-scale linear systems of algebraic equations arising from the discretization of randomly parametrized (or stochastic) elliptic partial differential equations (SPDEs). We analyze the proposed sparse conjugate gradient (CG) algorithm within the framework of inexact Krylov subspace methods, prove its convergence and study its abstract computational cost. Numerical studies conducted on stochastic diffusion models show that the proposed sparse CG algorithm outperforms the classical CG method when the sought solutions admit a sparse representation in a polynomial chaos basis. In such cases, the sparse CG algorithm recovers almost exactly the sparsity pattern of the exact solutions, which enables accelerated convergence. In the case when the SPDE solution does not admit a sparse representation, the convergence of the proposed algorithm is very similar to the classical CG method.     

Fast integral wavelet transform on a dense set of the time-scale domain

Summary. The objective of this paper is to introduce a fast algorithm for computing the integral wavelet transform (IWT) on a dense set of points in the time-scale domain. By applying the duality principle and using a compactly supported spline-wavelet as the analyzing wavelet, this fast integral wavelet transform (FIWT) is realized by applying only FIR (moving average) operations, and can be implemented in parallel. Since this computational procedure is based on a local optimal-order spline interpolation scheme and the FIR filters are exact, the IWT values so obtained are guaranteed to have zero moments up to the order of the cardinal spline functions. The semi-orthogonal (s.o.) spline-wavelets used here cannot be replaced by any other biorthogonal wavelet (spline or otherwise) which is not s.o., since the duality principle must be applied to some subspace of the multiresolution analysis under consideration. In contrast with the existing procedures based on direct numerical integration or an FFT-based multi-voice per octave scheme, the computational complexity of our FIWT algorithm does not increase with the increasing number of values of the scale parameter. Received March 3, 1994     

Effective computation of exact and analytic approximate solutions to singular nonlinear equations of Lane–Emden–Fowler type

The particular motivation of this work is to develop a computational method to calculate exact and analytic approximate solutions to singular strongly nonlinear initial or boundary value problems of Lane–Emden–Fowler type which model many phenomena in mathematical physics and astrophysics. A powerful algorithm is proposed based on the series representation of the solution via suitable base functions. The utilization of such functions converts the solution of a given nonlinear differential equation to the solution of algebraic equations. Error analysis and convergence of the method is presented. Comparisons with the other methods reveal validity, applicability and great potential of the method. Several physical problems are treated to illustrative the good performance and high accuracy of the technique.     

The algebraic degree of geometric optimization problems

In this paper we apply Galois methods to certain fundamentalgeometric optimization problems whose exact computational complexity has been an open problem for a long time. In particular we show that the classic Weber problem, along with theline-restricted Weber problem and itsthree-dimensional version are in general not solvable by radicals over the field of rationals. One direct consequence of these results is that for these geometric optimization problems there existsno exact algorithm under models of computation where the root of an algebraic equation is obtained using arithmetic operations and the extraction ofkth roots. This leaves only numerical or symbolic approximations to the solutions, where the complexity of the approximations is shown to be primarily a function of the algebraic degree of the optimum solution point.     

基于Hausdorff距离的模糊数互补判断矩阵排序研究

基于Bonissone近似计算、Hausdorff距离和模糊折衷型决策方法,给出带有梯形模糊数互补判断矩阵的一种排序方法。同时给出精确值、三角模糊数的互补判断矩阵转化为梯形模糊数互补判断矩阵的方法,因此本文方法同样适合于处理精确值、三角模糊数的互补判断矩阵的排序问题。最后用算例说明了计算过程。     

直觉模糊模型检测在工程决策上的应用

将直觉模糊Kripke结构扩展到加权直觉模糊Kripke结构,将直觉模糊计算树逻辑诱导到加权直觉模糊计算树逻辑;研究在此之上的直觉模糊期望测度和多属性工程决策问题。用加权直觉模糊Kripke结构的权值自然地刻画了工程问题中的成本和收益,直觉模糊测度量化工程进展的不确定性,用加权直觉模糊计算树逻辑描述不确定性工程属性约束。给出了基于直觉模糊模型检测的多属性工程寻优算法,并讨论了算法的复杂度。     

The structure of the norm system on fuzzy sets

In this paper, we shall define the norm system which provides the general model to fuzzy sets and systems. It is useful to deal with the operations and the extended operations of fuzzy sets by united method. Specifically, the extended operation's properties of fuzzy sets on the complete lattice are considered.     

A discrete optimization method based on a parameterization of a Grassmannian in multidimensional dichotomous data structuring

An approach to reducing large computational time in the problem of multidimensional dichotomous data structuring based on algebraic properties of finite geometries is proposed. A vector parameterization of the Grassmannian Gr₂(k, n) reducing memory expenditures and the number of operations required to solve this problem is introduced. A parallelization algorithm based on this parameterization and Gray coding which further reduces computational time is constructed.     

Operations and measurement of interval-valued fuzzy numbers based on the method of structured element

In this paper we introduced the definition of interval-valued fuzzy numbers based on the definition of interval-valued fuzzy set and the operations of real fuzzy numbers by extension principle, defined the operations of interval-valued fuzzy numbers and their distance, and gave their structured element representations and operations of them by using the fuzzy structured element method. The work of this paper is an expansion of the research of real fuzzy numbers.     

Interval optimization based line sampling method for fuzzy and random reliability analysis

For structural system with fuzzy variables as well as random variables, a novel algorithm for obtaining membership function of fuzzy reliability is presented on interval optimization based Line Sampling (LS) method. In the presented algorithm, the value domain of the fuzzy variables under the given membership level is firstly obtained according to their membership functions. Then, in the value domain of the fuzzy variables, bounds of reliability of the structure are obtained by the nesting analysis of the interval optimization, which is performed by modern heuristic methods, and reliability analysis, which is achieved by the LS method in the reduced space of the random variables. In this way the uncertainties of the input variables are propagated to the safety measurement of the structure, and the membership function of the fuzzy reliability is obtained. The presented algorithm not only inherits the advantage of the direct Monte Carlo method in propagating and distinguishing the fuzzy and random uncertainties, but also can improve the computational efficiency tremendously in case of acceptable precision. Several examples are used to illustrate the advantages of the presented algorithm.