文献中的词语分布、词型等级和风格计算

文献的语言风格是作者在语言运用方面的思维定势的体现,对于文献之间语言风格的差异,以前的研究大多采用定性分析的方式加以比较和概括,而在文献检索和文本分类领域需要得到量化的语言风格相似度。该文首先分析文献中词语分布的普遍规律,以先秦八部经典文献为观察语料,发现这些文献中的词语既呈离散分布,又呈集中分布;然后通过计算文献之间词型等级的相关系数,来获取量化的语言风格相似度,构建了八部文献之间的相似度矩阵,验证了语言风格的差异不仅体现在使用的常用词上,还更细微地体现在常用词的使用频率等级上。     

A method for stochastic multiple criteria decision making based on dominance degrees

This paper proposes a method for solving the stochastic multiple criteria decision making (SMCDM) problem, where consequences of alternatives with respect to criteria are represented by random variables with probability distributions. Firstly, definitions and related analysis of dominance degree of one probability distribution over another are given. Then, by calculating the dominance degrees, the dominance degree matrix of alternative pairwise comparisons with respect to each criterion is built. Further, using PROMETHEE II method, an overall dominance degree matrix of alternative pairwise comparisons is constructed, and a net flow of each alternative is calculated. Based on the obtained net flows, a ranking of alternatives is determined. Finally, numerical examples for the three cases are given to illustrate the use of the proposed method.     

Univariate marginal distribution algorithm dynamics for a class of parametric functions with unitation constraints

In this paper, we introduce a mathematical model for analyzing the dynamics of the univariate marginal distribution algorithm (UMDA) for a class of parametric functions with isolated global optima. We prove a number of results that are used to model the evolution of UMDA probability distributions for this class of functions. We show that a theoretical analysis can assess the effect of the function parameters on the convergence and rate of convergence of UMDA. We also introduce for the first time a long string limit analysis of UMDA. Finally, we relate the results to ongoing research on the application of the estimation of distribution algorithms for problems with unitation constraints.     

Application of fuzzy sets to manufacturing/distribution planning decisions in supply chains

In the real-world manufacturing/distribution planning decision (MDPD) integration problems in supply chains, the environmental coefficients and parameters are normally imprecise due to incomplete and/or unavailable information. This work presents a fuzzy linear programming approach based on the possibility theory. It applies this approach to solve multi-product and multi-time period MDPD problems with imprecise goals and forecast demand by considering the time value of money of related operating cost categories. The proposed approach attempts to minimize the total manufacturing and distribution costs by considering the levels of inventory, subcontracting and backordering, the available machine capacity and labor levels at each source, forecast demand and available warehouse space at each destination. This study utilizes an industrial case study to demonstrate the feasibility of applying the proposed approach to practical MDPD problems. The primary contribution of this paper is a fuzzy mathematical programming methodology for solving the MDPD integration problems in uncertain environments.     

基于平行截面上轮廓之间重构问题的研究

研究了基于平行截面上两多边形轮廓重构的基本问题,给出了利用体积最大化作为度量标准来求得一个"较好"并且合法的重构的目标函数,然后得出:其中一个多边形轮廓在其所在的截面上沿着法向平移、在截面内平移和在截面内等比例缩放都不影响最大化体积后的结果。该结论对于三维实体的可视化和几何造型领域具有重要的实用价值。     

A Jacobi-type method for computing balanced realizations

A new numerical scheme for computing balancing coordinate transformations in linear systems theory is presented. The method is closely related to the Jacobi method for diagonalizing symmetric matrices. Here the minimization of the sum of traces of the Gramians by orthogonal and nonorthogonal Jacobi-type rotations is considered. The algorithm is shown to be globally convergent to a balancing transformation that arranges the Hankel singular values in a prescribed ordering. Local quadratic convergence of the algorithm is shown.     

Solving multiple objective quasi-convex goal programming problems by linear programming

This study presents a novel means of resolving multiple objective goal programming (GP) problems with quasi-convex linear penalty functions. The proposed method initially expresses a quasi-convex function by the maximum operator of two convex functions, then solves it via a linear programming technique. The proposed method does not contain any zero–one variables; nor does it require dividing the multi-objective quasi-convex GP problem into large sub-problems as in conventional methods. Some illustrative examples are provided.     

A new neural network algorithm for planarization problems

To deal with the planarization problem widely used in many applications including routing very-large-scale integration （VLSI） circuits, this paper points out that only when its vertices are arranged in some specific order in a line can a planar graph be embedded on a line without any cross connections or cross edges. Energy function is proposed to meet the need of embedding a graph on a single line and route it correctly. A Hopfield network is designed according to the proposed energy function for such embedding and routing. The advantage of the proposed method is that it not only can detect if a graph is a planar one or not, but also can embed a planar graph or the maximal planar subgraph of a non-planar graph on a single line. In addition, simulated annealing is employed for helping the network to escape from local minima during the running of the Hopfield network. Experiments of the proposed method and its comparison with some existent conventional methods were performed and the results indicate that the proposed method is of great feasibility and effectiveness especially for the planarization problem of large graphs.     

运用EXCEL函数进行完全随机试验设计

完全随机设计的实质是将供试单位随机分组。该文通过对完全随机设计实质的分析,对运用EXCEL进行完全随机试验设计的方法进行了介绍。结果认为只要每一独立供试单位在组间随机排列,始终贯穿随机精神以最大限度地减少系统误差,灵活利用Excel的随机函数如RANDOM、RANDOMBETWEEN等和排序按钮,用任何一种方法都可以快速的进行完全随机试验设计。     

BP神经网络在剩余油分布预测中的应用研究

我国多数油田经过一次、二次采油后,仅能采出地下总储量的30%左右,这意味着有60%～70%的剩余石油仍然残留在地下成为剩余油。加强剩余油分布规律研究、提高石油采收率不仅有着可观的经济效应,而且关系到国家石油战略的安全。本研究应用神经网络的原理,基于BP网络使用MATLAB语言建立一个剩余油分布的预测系统。该系统通过学习在地理坐标和孔隙度之间建立一个非线性函数关系,以此来预测任何区域的孔隙度,再通过孔隙度与剩余油饱和度之间的关系达到剩余油分布预测的目的。