主成分分析的神经网络及其在木聚糖酶最适pH建模中的应用

木聚糖酶结构与功能、性质的关系错综复杂,传统的回归分析往往不能满足要求。本文采用主成分分析法对样本数据集进行预处理,将得到的新样本数据集输入神经网络,籍助于均匀设计（UD）,构建了木聚糖酶氨基酸组成和最适pH的模型。当学习速率为0．08、动态参数为0．7、Sigmoid参数为0．92,隐含层结点数为9时,模型的拟合残差为0．00109,对pH值拟合的平均绝对百分比误差为3．29％,同时具有良好的预测效果,预测的平均绝对误差为0．59个pH单位。比文献报道的用逐步回归方法更好。     

用神经网络模型预测饱和液体的传递性质

使用神经网络模型 ,对纯物质的饱和液体传递性质粘度、导热系数及表面张力与温度的函数关系进行预测。对常见的 35 0多种有机物的预测结果表明 ,在熔点到临界点的温度范围内 ,粘度、导热系数及表面张力的平均预测误差分别为 0 12 %、 0 0 9%及 0 0 3%。     

基于PSO和BP网络的LF炉钢水温度智能预测

研究将粒子群优化算法与BP神经网络相结合,建立新的钢水终点温度预报模型.确定加热功率、初始温度、精炼时间等8个影响钢水终点温度的主要因素作为神经网络的输入量.用粒子群优化算法优化神经网络参数,改善神经网络温度预测模型的收敛性能.实验结果表明,该算法可以提高预测速度和精度,预测结果误差不大于±5℃的炉次大于90%.     

基于PSO-BP的磁致伸缩式静力水准系统温度补偿研究

静力水准系统（Hydrostatic Leveling System,HLS）被广泛应用于基坑、桥隧和建筑物结构等工程的沉降监测。针对环境温度变化引起HLS测量误差的问题,对温度、温度变化速率和温度梯度三种温度误差影响因素进行详细分析,并提出了一种基于粒子群优化（PSO）算法和反向传播神经网络（BPNN）的温度补偿模型。通过BP神经网络对钵体液位值建立修正模型,利用PSO算法优化神经网络参数来提高拟合准确度与模型泛化能力。试验结果表明,利用多个影响因素建立的PSO-BP模型对HLS温度补偿后,使钵体液位值的均方误差和最大误差相比于补偿前平均降低80%以上,从而有效减少计算沉降的误差,极大提高HLS测量精度。     

热电偶RBF神经网络模型分布密度范围研究

本文提出的利用径向基神经网络（RBFNN）或广义回归神经网络（GRNN）建立热电偶特性模型的方法，解决了BP神经网络热电偶模型精度不高、重复训练时输出结果发生变化。有时出现奇异结果、不稳定等问题。模型算法简单，在一定参数范围内精度高，稳定性好，容易编程实现和便于实际应用。通过网络训练、仿真和误差分析，对RBFNN和GRNN模型参数及其适用范围进行了比较研究．找到了镍铬一康铜热电偶-270—1000℃模型和镍铬一镍硅热电偶0—1370℃模型的适宜的分布密度参数范围。     

基于有限元法的黑体腔高温传感器动态特性分析

基于有限元热分析法,建立了黑体腔三维有限元模型,分析了黑体腔结构参数、热物性参数、黑体腔初始预热温度对黑体腔测温过程中动态特性的影响。研究结果表明：黑体腔结构参数的改变直接影响黑体腔动态测温误差、动态响应时间、腔体发射率,进而影响黑体腔性能。黑体腔动态测温误差随着比热或密度的增大而增大。黑体腔初始预热温度对黑体腔动态测温影响较大,初始预热温度每增加100℃,最大测温误差减小50℃左右,动态响应时间减少5 s左右。     

基于误差预测的焦炉火道温度软测量模型

针对焦炉火道温度在线检测的问题,在分析焦炉火道温度特性的基础上,建立了一种基于误差预测的高精度焦炉火道温度软测量模型．首先分别建立了1元、2元和12元线性回归模型,对蓄顶温度和火道温度进行线性拟合;然后比较分析了三种回归子模型的特点．使用融合时间差分法的Elman神经网络,对线性回归模型中精度最高的12元模型的预测误差进行拟合和多步预测．采用专家经验将线性回归组合模型和融合时间差分法的Elman神经网络模型进行集成,最终获得了具有较高预测精度的焦炉火道温度软测量值．实际运行结果验证了该软测量模型的有效性．     

基于AP聚类RBF神经网络的改进算法及试验

针对AP聚类RBF神经网络在车辆动态称重应用中精度偏低问题,提出按一定步长,迭代增加偏向参数,以RBF神经网络测试误差为评价指标最终确定偏向参数的改进算法,使RBF神经网络获得合适的隐含层节点数;提出对测试样本进行归类插值分析,利用与测试样本至类代表点间距离最接近的两个训练样本实际连接权值,使RBF神经网络连接权值随测试样本改变的自适应功能.在车速10 km/h~50 km/h,温度16 ℃~29 ℃条件下,对5种不同载重车辆进行工程实测试验,构建车辆动态称重RBF神经网络模型,进行500次循环测试.试验表明,基于AP聚类RBF神经网络的改进算法使称重误差均值控制在0.06%以内,最大实时性均值为0.0223,能有效满足实际工程应用要求.     

直链聚合物的结构性质关系的模糊集理论方法建模

将模糊集理论方法用于直链聚合物的结构性质关系建模，构造了两个模型。一个是直链聚合物的基团法描述的结构参数与其12种性质间定量关系的模型(模型lF)；一个是直链聚合物的连接性指数描述的结构参数与其12种性质间定量关系的模型(模型2F)。两个模型给出的12种性质的拟合误差(拟合值与实验值间的标准偏差)分别是：V(298K)为15．1(模型lF)／58．4(模型2F)cc／mole，Ecch为6．580/17．838KJ／mole，δ为0．8225／3．2168(J／cc)^0.5，Fd为274／491J^0.5cm^1.5／mole，Tg为30／77K，Pt为23／66(cc／mole)(dyn／cm)^1/4，n为0．0125／0．095l，ξ为9／24 10^-6 cc／mole，UR为570／1240cm^l0／3(sec^1/3 mole)，UR为549／1428cm^10/3／(sec^1/3 mole)，Hqkam为5l1／1729gJ^1/3／mole^4/3，Yd,1／2为10．5／27．1K^*kg／mole。结果表明，所建立的模型可用于预测，且为聚合物结构性质关系建模引入了一个新的数学工具。     

基于混合优化算法的销轴传感器温度补偿及应用

针对应变片式销轴传感器井下工作过程中温度发生变化产生温度漂移,导致测量精度降低的问题,提出一种果蝇算法优化RBF神经网络的温度补偿模型,采用果蝇算法对神经网络的扩展参数进行全局优化,利用应力测试平台实测参数及神经网络非线性映射能力训练温度补偿模型。为验证温度补偿模型补偿效果及训练效率,对35℃下传感器进行实验测试。结果表明：35℃下,温度补偿模型补偿平均误差远小于单一算法补偿效果,验证了此方法具有较高的训练效率及补偿效果,能够提高传感器在不同温度、载荷作用下测量精度,同时将本文模型应用采煤机截割煤壁工作中,得到导向滑靴在采煤机行走截割煤壁过程中受力,为导向滑靴结构优化及提高采煤机可靠性和使用寿命提供依据。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。