回归型支持向量机调节熵函数法的区间扩张研究

为减小由于二进制编码的舍入误差对该问题计算结果的影响,对求解回归支持向量机的一种调节熵方法进行了区间扩张,讨论了区间函数的相关定理与收敛性.对设计的区间算法做了收敛性证明,并给出了数值实验,验证了方法与算法的可行性和有效性.     

小样本的均匀分布参数的区间估计和假设检验

本文提出了小样本的均匀分布参数的区间估计和假设检验方法 .数值模拟计算后效果良好     

The Order Completion Method for Systems of Nonlinear PDEs: Pseudo-topological Perspectives

By setting up appropriate uniform convergence structures, we are able to reformulate the Order Completion Method of Oberguggenberger and Rosinger in a setting that more closely resembles the usual topological constructions for solving PDEs. As an application, we obtain existence and uniqueness results for the solutions of arbitrary continuous, nonlinear PDEs.      

Effects of imperfect products on lot sizing with work in process inventory

The economic production quantity (EPQ) is one of the most widely known inventory control models that can be regarded as the generalized form of the Economic Order Quantity. However, the model is built on an unrealistic assumption that all the produced items need to be of perfect quality. Also, the introduction of work in process, WIP, as part of the inventory has been of lesser concern in developing inventory models. This paper attempts to develop the economic production quantity considering work in process inventory and manufacturing imperfect products that may be either reworkable or non-reworkable. The non-reworkable imperfect products are sold at a reduced price. This paper introduces a new model for this problem.     

Theorems on products of EPr matrices,II

This paper gives necessary and sufficient conditions that the product of EPr matrices with entries from an arbitrary field be EPr. Results about the Reverse Order Law for generalized inverses of products of these matrices are included.     

A novel variable step size fractional order incremental conductance algorithm to maximize power tracking of fuel cells

The maximum power tracking of Proton Exchange Membrane Fuel Cells (PEMFC) is important for the optimization of fuel cell system design. It is necessary to operate a fuel cell at maximum power to ensure full efficiency. This study presents a novel Fractional Order Incremental Conductance Algorithm (FOINC) with variable step size control which can be used for maximum power point tracking in the design of fuel cells. The method has high maximum power point tracking speed and good steady-state response, and does not require extra sensing elements for different fuel cell equipment. When compared to the traditional Incremental Conductance (INC) and Perturbation and Observation (P&O) methods, the system simulation results show the method to be feasible and effective.     

Statistical evaluation of forming limit diagram for annealed Al 1350 alloy sheets using first order reliability method

This paper investigates the formability and forming limit curve of aluminium alloy sheet of grade Al 1350 with respect to annealing temperature and strain conditions through statistical approach. The uncertainty of forming limit curve (FLC) due to anisotropy parameter and strain hardening exponent have also been taken into consideration. The plastic instability criteria and its relevant equations given by Hill have been used to construct the theoretical FLC which is compared with experimental FLC. The stochastic modeling has been made on the statistical evaluation of the FLC with a high confidence level. First Order Reliability Method (FORM) and Monte-Carlo simulation (MCS) methods have been used to compare the probability of the data points determining FLC by considering normal distribution of material properties.     

基于最大满意度的区间混合判断矩阵排序方法

区间混合判断矩阵对表达决策者的判断信息很有帮助,然而区间混合判断矩阵尚未引起学者的足够重视.定义了一致性乘型区间混合判断矩阵和一致性加型区间混合判断矩阵,并基于最大满意度的思想,提出了求解区间混合判断矩阵的乘型和加型最大满意度模型和一致性指标,分析讨论了最大满意度模型的优点,最后通过算例验证了该模型的正确性和适用性,具有一定的理论和实际应用价值.     

A Benders decomposition approach for the robust spanning tree problem with interval data

The robust spanning tree problem is a variation, motivated by telecommunications applications, of the classic minimum spanning tree problem. In the robust spanning tree problem edge costs lie in an interval instead of having a fixed value.Interval numbers model uncertainty about the exact cost values. A robust spanning tree is a spanning tree whose total cost minimizes the maximum deviation from the optimal spanning tree over all realizations of the edge costs. This robustness concept is formalized in mathematical terms and is used to drive optimization.This paper describes a new exact method, based on Benders decomposition, for the robust spanning tree problem with interval data. Computational results highlight the efficiency of the new method, which is shown to be very fast on all the benchmarks considered, and in particular on those that were harder to solve for the methods previously known.     

Analytical form of optimal control and reachability sets in a resource allocation problem

This article investigates a resource allocation problem with a clear economic interpretation. The process dynamics is described in terms of a linear production function. An optimal solution of the control problem is constructed in analytical form. Equal and different positive depreciation rates are considered. The optimal solution is obtained by Pontryagin's maximum principle, which provides a methodologically interesting approach. An alternative approach based on a special representation of the functional is also considered. The reachability set is constructed assuming equal depreciation rates for the controlled plant. An explicit analytical expression is obtained for the optimal value of the functional in terms of the problem parameters. This expression is useful for future analysis. __________ Translated from Prikladnaya Matematika i Informatika, No. 27, pp. 80–99, 2007.     

Third order efficiency implies fourth order efficiency: A resolution of the conjecture of J. K. Ghosh

Under suitable regularity conditions, it is shown that a third order asymptotically efficient estimator is fourth order asymptotically efficient in some class of estimators in the sense that the estimator has the most concentration probability in any symmetric interval around the true parameter up to the fourth order in the class. This is a resolution of the conjecture by Ghosh (1994, Higher Order Asymptotics, Institute of Mathematical Statistics, Hayward, California). It is also shown that the bias-adjusted maximum likelihood estimator is fourth order asymptotically efficient in the class.     

The influence of sample extremes on the maximum of partial sums of independent random variables

Many papers exist dealing with the distribution of the maximum of partial sums of independent random variables and studying the relationship between the sums and the sample extremes (see [L. Takacs,Combinator Methods in the Theory of Stochastic Processes, Wiley, New York (1967)], [J. Calambos,The Asymptotic Theory of Extreme Order Statistics, Wiley, New York (1978)]). The present paper deals with the effect the sample extremes have on the distribution of the maximum of sums of independent random variables. Proceedings of the Seminar on Stability Problems for Stochastic Models, Moscow, 1993     

区间二次规划在确定模糊评价因素权向量中的应用

利用区间二次规划方法确定模糊综合评判中评价因素的模糊权向量，它的原理是：以区间的概念为基础。利用区问相离度公式计算使主观偏好值与客观偏好值的总差距最小的权向量就是所求的评价因素的模糊权向量。     

A method for group decision-making based on determining weights of decision makers using TOPSIS

In general, weights of decision makers (DMs) play a very important role in multiple attribute group decision-making (MAGDM), how to measure the weights of DMs is an interesting research topic. This paper presents a new approach for determining weights of DMs in group decision environment based on an extended TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method. We define the positive ideal solution as the average of group decision. The negative ideal solution includes two parts: left and right negative ideal solution, which are the minimum and maximum matrixes of group decision, respectively. We give an example to illustrate the developed approach. Finally, the advantages and disadvantages of this study are also compared.     

未确知测度区间评价理论及其应用

根据未确知测度理论,提出未确知测度区间的概念,建立未确知测度区间评价模型,并获得较为成功的应用.     

Inference for a progressive stress model from Weibull distribution under progressive type-II censoring

Based on progressively type-II censored samples, this paper considers progressive stress accelerated life tests when the lifetime of an item under use condition follows the Weibull distribution with a scale parameter satisfying the inverse power law. It is assumed that the progressive stress is directly proportional to time and the cumulative exposure model for the effect of changing stress holds. Point estimation of the model parameters is obtained graphically by using Weibull probability paper plot that serves as a tool for model identification and also by using the maximum likelihood method. Interval estimation is performed by finding approximate confidence intervals (CIs) for the parameters as well as the studentized-t and percentile bootstrap CIs. Monte Carlo simulation study is carried out to investigate the precision of the estimates and compare the performance of CIs obtained. Finally, two examples are presented to illustrate our results.     

Improving Interval Analysis Bounds by Translations

We explore how a simple linear change of variable affects the inclusion functions obtained with Interval Analysis methods. Univariate and multivariate polynomial test functions are considered, showing that translation-based methods improve considerably the bounds computed by standard inclusion functions. An Interval Branch-and-Bound method for global optimization is then implemented to compare the different procedures, showing that, although with times higher than those given by Taylor forms, the number of clusters and iterations is strongly reduced.     

GO-MOCE: Greedy Order Method of Conditional Expectations for Max Sat

In this paper we present and study a new algorithm for the Maximum Satisfiability (Max Sat) problem. The algorithm is based on the Method of Conditional Expectations (MOCE, also known as Johnson’s Algorithm) and applies a greedy variable ordering to MOCE. Thus, we name it Greedy Order MOCE (GO-MOCE). We also suggest a combination of GO-MOCE with CCLS, a state-of-the-art solver. We refer to this combined solver as GO-MOCE-CCLS.We conduct a comprehensive comparative evaluation of GO-MOCE versus MOCE on random instances and on public competition benchmark instances. We show that GO-MOCE reduces the number of unsatisfied clauses by tens of percents, while keeping the runtime almost the same. The worst case time complexity of GO-MOCE is linear. We also show that GO-MOCE-CCLS improves on CCLS consistently by up to about 80%.We study the asymptotic performance of GO-MOCE. To this end, we introduce three measures for evaluating the asymptotic performance of algorithms for Max Sat. We point out to further possible improvements of GO-MOCE, based on an empirical study of the main quantities managed by GO-MOCE during its execution.     

A branch and bound algorithm for the robust spanning tree problem with interval data

The robust spanning tree problem is a variation, motivated by telecommunications applications, of the classic minimum spanning tree problem. In the robust spanning tree problem edge costs lie in an interval instead of having a fixed value.Interval numbers model uncertainty about the exact cost values. A robust spanning tree is a spanning tree whose total cost minimizes the maximum deviation from the optimal spanning tree over all realizations of the edge costs. This robustness concept is formalized in mathematical terms and is used to drive optimization.In this paper a branch and bound algorithm for the robust spanning tree problem is proposed. The method embeds the extension of some results previously presented in the literature and some new elements, such as a new lower bound and some new reduction rules, all based on the exploitation of some peculiarities of the branching strategy adopted.Computational results obtained by the algorithm are presented. The technique we propose is up to 210 faster than methods recently appeared in the literature.     

Modular global optimisation in chemical engineering

Chemical Engineering design and analysis is dominated by the use of modular computational systems restricting the use of rigorous global optimisation techniques. Other engineering domains also exploit modularity in order to break down complex tasks to allow the use of legacy codes, to protect intellectual property, and to allow large teams to work on problems. By casting modules in a generic form such systems could be recast to incorporate interval based methods. In this paper we explore the use of five interval contraction methods to improve the performance of interval based optimization of modular process design systems: consistency methods, constraint propagation, Interval Gaussian elimination, Interval Newton and Linear Programming. It is shown that the Linear Programming contractor provides the greatest value in contracting the intervals and that constraint propagation and Interval Gaussian elimination (as implemented here) provides less of an impact. Other contractors do provide value and the LP contractor will be of less value as the problem size increases so it is necessary to include a number of contractors which can be done at small computational cost. A number of challenges are outlined which need to be addressed before there can be routine use of interval global optimization in modular systems.