基于MPSO-BP算法的四电极电化学气体传感器温度补偿研究

针对四电极电化学气体传感器的测量精度极易受环境温度影响的问题,提出一种基于粒子群优化-BP神经网络算法（PSO-BP）的温度补偿方法。利用改进的PSO算法（MPSO）对BP神经网络的权值和阈值进行优化,构造四电极电化学气体传感器的温度补偿模型,并设计了气体传感器测试系统。实验结果表明,MPSO-BP算法可有效提高BP神经网络的收敛速度和泛化能力;基于MPSO-BP算法的四电极气体传感器温度补偿模型,可将其温度补偿误差控制在0.1%以内。     

基于分段融合的压阻式传感器温度补偿方法

针对硅压阻式压力传感器在工程应用中受环境温度和压力的影响产生漂移,影响测量精度等问题.提出一种基于粒子群优化RBF神经网络与最小二乘法融合的温度补偿模型.使用粒子群算法对常规RBF神经网络的权值和阙值进行优化,提高神经网络的泛化性能和训练效率,增强传感器非线性段温度补偿的效果;使用最小二乘法对线性段进行温度补偿,提高整体模型的补偿效率.以飞思卡尔24 PC型压力传感器进行补偿实验,结果表明:对比优化前的神经网络和最小二乘方法,利用本文方法进行温度补偿,耗时短,总体误差低于其他两种方法.传感器在整个温度区间和压力测试点下的输出基本不受影响,补偿效果明显,数据精度符合课题实验的要求.     

基于混合优化算法的压力传感器温度补偿

针对压阻式压力传感器存在温度漂移,其测量精度受温度影响很大的问题,使用最小二乘拟合方法与RBF神经网络共同建立压力传感器温度补偿模型.针对低温和高温区域使用RBF神经网络进行补偿,对中间线性区域使用最小二乘拟合方法进行补偿.同时为了提高RBF神经网络拟合效果,使用进化算法和下降梯度算法优化RBF神经网络参数.实验结果表明,本文使用方法与单纯使用RBF神经网络或最小二乘拟合方法进行温度补偿,具有更高的训练效率和温度补偿效果,能够提高压力传感器在各种环境下的测量精度和工作可靠性.     

基于RBFNN的称重传感器温度误差补偿

称重传感器存在因环境温度不同导致的非线性误差,需要进行补偿.阐述了称重传感器的温度误差机理,提出了一种基于径向基函数神经网络(RBFNN)的称重传感器温度误差补偿方法,并给出了训练算法.采用该方法,利用量程为100kg的称重传感器,在0～60℃范围内进行温度误差补偿实验.实验表明:采用这种方法补偿后,称重传感器温度误差...     

RBF神经网络热式气体流量计温度补偿

为了解决热式气体流量计测量电路中采用硬件温度补偿成本高且精度不够等问题,利用神经网络的特点,设计了一种基于径向基函数(RBF)神经网络的软件温度补偿方法.实验表明:通过RBF神经网络温度补偿,有效地抑制了温度对流量计测量结果的影响,实现了环境温度梯度变化下气体流量测量的准确性和稳定性,测量准确度达到1.0级,且重复性好.     

基于小波神经网络的压力传感器温度补偿方法

介绍了硅压阻式压力传感器温度误差产生的原因及其特点,在比较了多种神经网络优缺点的基础上,提出了一种利用小波神经网络对压力传感器温度误差及非线性误差进行补偿的方法.该网络与BP神经网络相比,具有更快的收敛速度和更好的补偿精度.经过实验证明:该网络能够有效地补偿压力传感器的温度非线性误差,在-40～60℃范围内,使温度误差从原来的5.4%降到了0.2%.     

基于RBF神经网络的单一催化传感器检测混合气体研究

根据催化传感器在不同的工作温度下具有不同气体检测灵敏度的特点,提出基于恒温检测与RBF神经网络的单一热催化传感器检测可燃混合气体的新方法.采用动态学习算法的RBF神经网络建立了多种可燃气体分析的数学模型.通过对甲烷,一氧化碳和氢气三种气体混合的样本进行实验,结果表明所研究的方法可以较好地实现单一催化传感器对多种可燃混合气体的分析.     

基于神经网络的传感器非线性误差校正

介绍了用神经网络校正传感器系统非线性误差的原理和方法,提出了一种基于RBF神经网络的传感器非线性校正模型及其算法,并与采用BP神经网络校正非线性误差进行了比较,并给出一个仿真实验,实验结果表明:采用RBF神经网络的传感器非线性校正精度和网络训练速度均大大优于BP神经网络,能满足实用要求.     

RBF神经网络在红外CO_2传感器压力补偿中的应用研究

在红外CO2传感器的测量过程中,环境总压是一个重要的影响因素。在环境总压变化的情况下做好压力补偿得出正确的CO2气体分压值,对提高传感器的测量精度有重要意义。提出一种基于聚类和梯度法的径向基函数(RBF)神经网络方法,利用它的局部逼近特性,建立起其在红外CO2传感器的非线性压力补偿中的网络模型。实验结果表明:该应用收到了良好的效果。     

矿井CO浓度的支持向量机数据融合检测方法

针对检测矿井一氧化碳（CO）含量时,电化学传感器输出受到矿井大气中甲烷气体影响的问题,提出了一种基于支持向量机（SVM）数据融合的CO浓度检测方法。该方法将催化传感器与电化学传感器构成传感器对,利用能够从全局意义上逼近任意非线性关系的支持向量机对传感器对的输出信号进行非线性数据融合,构建了矿井一氧化碳浓度检测模型。实验结果表明,该方法的平均绝对百分比误差为0.88%,均方根误差为1.32 ppm,有效地消除了甲烷对CO电化学传感器的影响,实现了矿井CO浓度的精确检测。     

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。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.