A novel approach to adaptive relational association rule mining

The paper focuses on the adaptive relational association rule mining problem. Relational association rules represent a particular type of association rules which describe frequent relations that occur between the features characterizing the instances within a data set. We aim at re-mining an object set, previously mined, when the feature set characterizing the objects increases. An adaptive relational association rule method, based on the discovery of interesting relational association rules, is proposed. This method, called ARARM (Adaptive Relational Association Rule Mining) adapts the set of rules that was established by mining the data before the feature set changed, preserving the completeness. We aim to reach the result more efficiently than running the mining algorithm again from scratch on the feature-extended object set. Experiments testing the method's performance on several case studies are also reported. The obtained results highlight the efficiency of the ARARM method and confirm the potential of our proposal.     

Improving Short-Circuit Current Capacity, Resistance, and Breaking Load of OPGW Constructions by Modifying Aluminium Alloy With AlB2

This article presents a method that can be applied to molten AA-6101 alloy to improve electrical properties of the aluminium part of the optical ground wire (OPGW) used in overhead transmission lines to protect phase conductors from lightning strike and to transmit signals and data. AA-6101 alloy in casting of the log as 6 m length and 178 mm diameter for extrusion has been inoculated by AlB₂ to decrease detrimental effects of Cr, Ti, V, and Zr on the conductivity of the material. After inoculation, improved billets were extruded as 9.5 mm diameter feedstock. Required wires drawn from the feedstock according to the construction types of OPGW to be tested were exposed to aging at 175°C, 6 h (T-8). Upon completion of the back-twist and performing-type stranding process, resistance, and short-circuit current capacity and breaking load of the OPGW 88/44 constructions with other metal combinations have been examined and tested to show improvement. Results are summarized in tables and graphically.     

大坝安全监控专家系统中的知识处理

在介绍产生式规则及其数学模型的基础上，论述了用成熟的关系数据库 技术来表示和存储产生式规则表示的专家知识的方法，较好地解决了知识的存储和管理问题 。同时，利用关系数据库中实体间的关系，很容易将分散存储的规则元素组合成规则供推理 时使用。在分析了大坝安全监控专家系统知识特点的基础上举例说明了用关系数据库表 示产生式规则的具体方法。     

Extrapolation of fuzzy values from incomplete data bases

This paper presents different approaches which enable a data base management system to obtain a plausible fuzzy estimate for an attribute value of an item for which the information is not explicitly stored in the data base. This can be made either by a kind of analogical reasoning from information about particular items or by means of expert rules which specify the (fuzzy) sets of possible values of the attribute under consideration, for various classes of items. Another kind of expert rules enables the system to compute an estimate from the attribute value of another item provided that, in other respects, this latter item sufficiently resembles the item, the value of which we are interested in; then these expert rules are used either for controlling the analogical reasoning process or for enlarging the scope of application of the first kind of expert rules. The different approaches are discussed in the framework of possibility theory.     

水库最优调度规则的神经网络模型

利用人工神经网络的非线性决策特点，提出了水库（电站）最优调度规则的人工神经网络模型，以四川宝珠寺水电站为例，进行其最优调度规则的模拟，研究结果表明了模型的合理性，可行性及实用性。     

关于Smarandache可乘函数的均值研究

本文的主要目的是利用初等方法研究Smarandache可乘函数在简单数集中的均值性质,并给出一个有趣的渐近公式。     

A family of lower- and higher-order transversal linearization techniques in non-linear stochastic engineering dynamics

Sample pathwise numerical integration of noise-driven engineering dynamical systems cannot generally be performed beyond a limited level of accuracy, especially when the noise processes are modelled using (filtered) white noises. Recently, a locally transversal linearization (LTL) strategy has been proposed by the author (Proc Roy Soc London A 2001; 457 :539–566) for direct integration of deterministic and stochastic non-linear dynamical systems. The present effort is focussed on a host of extensions along with detailed theoretical error analyses of the linearization approach, especially as applied to problems in non-linear stochastic engineering dynamics. Thus, to begin with, estimates of local and global error orders in the basic LTL scheme are obtained separately for the displacement and velocity vectors when the system is driven either by a set of additive noises or by an arbitrary combination of (independently evolving) additive and multiplicative noises. Following this, a new family of higher-order LTL schemes is proposed in order to improve upon the basic LTL method and the associated error orders are established. A stepwise implementation of the lower- and higher-order versions of the LTL method, along with certain computational aspects, is also outlined. The proposed schemes are numerically illustrated, to a limited extent, for a single degree-of-freedom (SDOF) and a two degree-of-freedom (TDOF) non-linear engineering systems under additive and/or multiplicative white noise excitations. Copyright © 2004 John Wiley & Sons, Ltd.     

广义杠杆规则及其在配方计算中的应用

作者将相图中的一维杠杆规则推广至多元配料系统而成为广义杠杆规则，并利用这一规则对配方计算中解的可行域问题进行了深入的讨论，给出了几何解释及工艺诠释，对配方设计有一定的指导作用。     

Efficient and accurate approach for powder compaction problems

 In this paper, a new approach for powder cold compaction simulations is presented. A density-dependent plastic model within the framework of finite strain multiplicative hyperelastoplasticity is used to describe the highly nonlinear material behaviour; the Coulomb dry friction model is used to capture friction effects at die-powder contact; and an Arbitrary Lagrangian–Eulerian (ALE) formulation is used to avoid the (usual) excessive distortion of Lagrangian meshes caused by large mass fluxes. Several representative examples, involving structured and unstructured meshes are simulated. The results obtained agree with the experimental data and other numerical results reported in the literature. It is shown that, contrary to other Lagrangian and adaptive h-remeshing approaches recently reported for this type of problems, the present approach verifies the mass conservation principle with very low relative errors (less than 1% in all ALE examples and exactly in the pure Lagrangian examples). Moreover, thanks to the use of an ALE formulation and in contrast with other simulations, the presented density distributions do not present spurious oscillations. Received: 20 March 2002 / Accepted: 15 October 2002 The partial financial support of the Ministerio de Ciencia y Tecnología (grant number DPI 2001-2204) is gratefully acknowledged.     

基于约束优化的联想记忆模型学习算法

本文提出了一种对称互连神经元网络的学习策略,利用全局约束优化方法确定连接权。优化过程采用了梯度下降技术。这种学习算法可以保证训练样本成为系统的稳定吸引子,并且具有优化意义上的最大吸引域。本文讨论了网络的存储容量,训练样本的渐近稳定性和吸引域大小。计算机实验结果说明了学习算法的优越性。