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.     

蒙特卡罗法及其在射弹散布仿真中的应用

作战仿真的真实性需要对抗双方火力射击效果的真实体现。文中提出了一种利用蒙特卡罗法进行射弹散布仿真的方法 ,并将结果与实际情况进行了比较。该方法已用于装甲兵数字化作战仿真实验室的作战仿真中     

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。     

Efficient multitasking in a dual-core CPU system

The paper offers an associative-neural-net method to optimize resource allocation between independent tasks in a multiprocessor system. In the case of a dual-core CPU the method allows the task to be fully solved in O(M) operations. The text was submitted by the authors in English.     

Distributed key management for dynamic groups in MANETs

Most existing solutions to group security in Mobile Ad Hoc Networks (MANETs) rely on a multicast Core Based Tree (CBT) for key distribution. Such solutions, although suitable for systems with low mobility and static characteristics, are unsuitable for dynamic and sparse groups with changing neighborhoods. In this paper, we propose an entirely decentralized key generation mechanism, employing a central trusted entity only during initialization. Using our approach, keys can be established between group members with absolutely no prior communication. The solution relies on threshold cryptography and introduces a novel concept of Node-Group-Key (NGK) mapping. We have provided an extensive analytical model for the computations involved and communication costs and have also provided a lie detection mechanism. Simulation results show appreciable performance improvement and enhanced robustness.     

Semiempirical and ab initio conformational analysis of 2-methylene-8,8-dimethyl-1,4,6,10-tetraoxaspiro[4.5] decane with application of GIAO-SCF methods to NMR spectrum interpretation

The GIAO-SCF method for calculating isotropic nuclear magnetic shielding values has been utilized to explain certain features in the ¹H-NMR spectrum of 2-methylene-8,8-dimethyl-1,4,6,10-tetraoxaspiro[4.5] decane. Population distributions of the low-energy conformers based on their ab initio energies were used to produce weighting factors for the individual calculated shielding values to calculate the weighted average of the shielding values for a complete set of conformers. The differences in ¹H chemical shifts between the hydrogens of the two methyl groups and between the axial and equatorial hydrogens in 2-methylene-8,8-dimethyl-1,4,6,10-tetraoxaspiro[4.5] decane were shown to be due to energy differences between the chair and boat orientations of the six-membered ring and contribution from a twist-boat conformation. Results suggest a hypothesis that intramolecular differences in chemical shift might be calculated to a greater degree of accuracy than chemical shifts calculated relative to a standard.     

Predicting dam failure risk for sustainable flood retention basins: A generic case study for the wider Greater Manchester area

This study aims to provide a rapid screening tool for assessment of sustainable flood retention basins (SFRBs) to predict corresponding dam failure risks. A rapid expert-based assessment method for dam failure of SFRB supported by an artificial neural network (ANN) model has been presented. Flood storage was assessed for 110 SFRB and the corresponding Dam Failure Risk was evaluated for all dams across the wider Greater Manchester study area. The results show that Dam Failure Risk can be estimated by using the variables Dam Height, Dam Length, Maximum Flood Water Volume, Flood Water Surface Area, Mean Annual Rainfall (based on Met Office data), Altitude, Catchment Size, Urban Catchment Proportion, Forest Catchment Proportion and Managed Maximum Flood Water Volume. A cross-validation R² value of 0.70 for the ANN model signifies that the tool is likely to predict variables well for new data sets. Traditionally, dams are considered safe because they have been built according to high technical standards. However, many dams that were constructed decades ago do not meet the current state-of-the-art dam design guidelines. Spatial distribution maps show that dam failure risks of SFRB located near cities are higher than those situated in rural locations. The proposed tool could be used as an early warning system in times of heavy rainfall.