Quantitative analysis of Ni effect on CCT diagrams of novel air-cooled bainite steels using artificial neural network models

The quantitative effect of Ni content on continuous cooling transformation （CCT） diagrams of novel air-cooled bainite steels was analyzed using artificial neural network models. The results showed that Ni may retard the high- and medium-temperature transformation and martensite transformation. The results conform to the materials science theories.     

Specification methods for material-handling control algorithms in flexible manufacturing systems

Good methods are needed to specify, test, and debug material-handling control logic. This article surveys a number of representative methods for defining and describing control algorithms for programmable material-handling equipment used in flexible manufacturing systems. The methods are evaluated with regard to their suitability for communication between people and as bases for interfaces to automatic program generators. It is concluded that no single method is entirely satisfactory. Three methods (position diagrams, function block diagrams, and operation networks) have potential to be combined into an effective hybrid approach that minimizes the need for the user to switch between various conceptual models.     

Synthesis and characterization of an interpenetrating polymer network composed of poly(methacrylic acid) and poly(vinyl alcohol)

Temperature and pH‐responsive interpenetrating polymer network (IPN) hydrogels, constructed with poly(methacrylic acid) (PMAA) and poly(vinyl alcohol) (PVA), by a sequential IPN method, were studied. The characterization of IPN hydrogels was investigated by Fourier‐transform infrared spectroscopy, differential scanning calorimetry (DSC) and swelling under various conditions. The IPN hydrogels exhibited relatively high swelling ratios, in the range 230–380 %, at 25 °C. The swelling ratios of the PMAA/PVA IPN hydrogels were pH and temperature dependent. DSC was used for the quantitative determination of the amounts of freezing and non‐freezing water. The amount of free water increased with increasing PMAA content in the IPN hydrogels. Copyright © 2004 Society of Chemical Industry     

应用遗传神经网络研究低渗透储层成岩储集相—以胜利渤南油田三区沙河街组为例

以渤南油田三区沙河街组为例,应用遗传人工神经网络模式识别方法,开展了低渗透储层成岩储集相的研究。该工作是在储集层沉积相、成岩作用研究的基础上,选用流动层带指标、孔隙度、渗透率、粒度中值、泥质含量、孔喉半径均值和变异系数等7项参数,采用神经网络模式识别方法,通过建立遗传神经网络的学习及预测模型,对渤南油田三区沙河街组进行了成岩储集相识别,识别出4类成岩储集相:不稳定组分强溶解次生孔隙成岩储集相、碳酸盐胶结物溶解次生孔隙成岩储集相、强压实强胶结残余粒间孔成岩储集相和极强压实强胶结致密成岩储集相。Ⅰ类储集相的储集性能最好,Ⅳ类最差,为非储层或差储层。     

Optimal ensemble construction via meta-evolutionary ensembles

In this paper, we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to correctly classify test points, and are given extra rewards for getting difficult points right. Ensembles consisting of multiple classifiers also compete for member classifiers, and are rewarded based on their predictive performance. In this way we aim to build small-sized optimal ensembles rather than form large-sized ensembles of individually-optimized classifiers. Experimental results on 15 data sets suggest that our algorithms can generate ensembles that are more effective than single classifiers and traditional ensemble methods.     

地震勘探技术在焉耆盆地勘探开发中的合理应用探讨

地震勘探技术应用可以分为以二维地震研究构造为主的地震勘探初级阶段、以地震地层学为主的地震勘探中级阶段、以三维地震油藏静态描述为主的地震勘探高级阶段、以地震储层研究为主的开发地震妆级阶段和以四维地震进行油藏监测为主的开发地震高级阶段。针对5个不同阶段的地质条件和地质任务，选择使用合理的地震勘探技术是有效提高勘探开发效益的重要途径。焉耆盆地的勘探开发体现了以地震勘探为主的思路，在勘探开发过程中重视了针对不同勘探开发阶段和不同的地质 地震技术，因此，在早期勘探开发中取得了很好的经济效益。     

Wavefront reduction using graphs,neural networks and genetic algorithm

This paper presents an algorithm for nodal numbering in order to obtain a small wavefront. Element clique graphs are employed as the mathematical models of finite element meshes. A priority function containing five vectors is used, which can be viewed as a generalization of Sloan's function. These vectors represent different connectivity properties of the graph models. Unlike Sloan's algorithm, which uses two fixed coefficients, here, five coefficients are employed, based on an evaluation by artificial neural networks. The networks weights are obtained using a simple genetic algorithm. Examples are included to illustrate the performance of the present hybrid method. Copyright © 2004 John Wiley & Sons, Ltd.     

神经网络在缺陷识别中的应用

为了准确、快速地进行缺陷识别，介绍了一种新型的前馈神经网络模型，即径向基概率神经网络。与以往的算法相比，该方法具有分类识别精度高且速度快的优点。仿真获得了很好的结果。     

A new distributed approximation algorithm for constructing minimum connected dominating set in wireless ad hoc networks

In recent years, constructing a virtual backbone by nodes in a connected dominating set (CDS) has been proposed to improve the performance of ad hoc wireless networks. In general, a dominating set satisfies that every vertex in the graph is either in the set or adjacent to a vertex in the set. A CDS is a dominating set that also induces a connected sub‐graph. However, finding the minimum connected dominating set (MCDS) is a well‐known NP‐hard problem in graph theory. Approximation algorithms for MCDS have been proposed in the literature. Most of these algorithms suffer from a poor approximation ratio, and from high time complexity and message complexity. In this paper, we present a new distributed approximation algorithm that constructs a MCDS for wireless ad hoc networks based on a maximal independent set (MIS). Our algorithm, which is fully localized, has a constant approximation ratio, and O(n) time and O(n) message complexity. In this algorithm, each node only requires the knowledge of its one‐hop neighbours and there is only one shortest path connecting two dominators that are at most three hops away. We not only give theoretical performance analysis for our algorithm, but also conduct extensive simulation to compare our algorithm with other algorithms in the literature. Simulation results and theoretical analysis show that our algorithm has better efficiency and performance than others. Copyright © 2005 John Wiley & Sons, Ltd.     

Comment on Greenwood (2007): Solving the puzzle of structure/function relations in the aging brain?

Neuroimaging experiments have shown that prefrontal regions of the brain, which have the most age-related volume loss, are also the regions most likely to be more active in older adults than in younger adults. In an attempt to solve this puzzle, P. M. Greenwood (see record 2007-15625-001) has proposed a cascade that flows from age-related atrophy in the brain to changed processing strategies that result in plastic changes in regions adjacent and contralateral to the atrophic areas, culminating in greater functional activity. This hypothesis should stimulate research into these mechanisms and hopefully will ultimately inform researchers' ability to rehabilitate cognitive disorders in the elderly. (PsycINFO Database Record (c) 2010 APA, all rights reserved)