Adaboost集成BP神经网络在传感器阵列检测系统中的应用

针对目前常见的多元有害气体检测问题,设计并搭建了一种基于传感器阵列和集成 BP神经网络相结合的传感器阵列检测系统。在该系统中采用集成BP神经网络对传感器阵列的三种混合有害气体的响应信号进行回归分析。为了提高集成BP神经网络的预测准确性,又利用Adaboost算法对集成BP神经网络进行了优化。结果显示：该系统能够准确地检测气体组分,通过Adaboost算法对集成BP神经网络优化后,预测的平均相对误差小于2%,能够有效解决气体传感器的交叉敏感问题,提高传感器的选择性。     

飞控系统传感器故障诊断的神经网络方法研究

BP神经网络对于飞行控制系统传感器故障诊断是一种有效的故障模式识别方法;在标准BP神经网络的基础上,提出了一种新的BP改进算法——自适应FMBP算法(SAFMBP),用以消除标准BP网络收敛速度慢及易陷入局部极小等缺点,并且建立了飞行控制系统仿真模型和传感器常见故障模型,采用基于神经网络模式分类的故障诊断方法,应用改进的BP神经网络(SAFMBP)进行飞控系统传感器的故障诊断,最后给出了仿真诊断实例。     

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.     

基于BP神经网络的多传感器信息融合研究

BP网络是应用最广的一种人工神经网络,将BP神经网络应用到压力检测领域的温度等非线性补偿,具有重要的实用价值,对压力检测精度的改进效果显著;从传感器信息融合的角度看,神经网络就是一个融合系统;通过对神经网络基本理论的阐述,针对研究对象将BP神经网络原理与多传感器信息融合技术有机集合起来,提出了基于BP神经网络的二传感器信息融合模型及改进算法,建立了BP神经网络训练标准样本库,并对该网络模型进行主要技术指标的测试和仿真工作,测试结果表明构建的模型及其改进算法能很好地满足了高精度压力检测仪的指标要求.     

PSO-BP网络模型在温室数据融合中的应用研究

由于温室的众多要素之间是相互制约、互相配合的,为了形成一个准确、合理的判断,将PSO算法的全局优化能力和BP神经网络良好的非线性映射能力相结合,优化BP神经网络的权值和阈值,提出了一种基于PSO的BP网络数据融合算法,并利用该算法对温室多传感器(温度传感器、湿度传感器和光照度传感器)同时检测到的数据进行融合。仿真结果表明:基于PSO-BP网络的数据融合算法能够获得温室准确有效的信息,提高温室控制的有效性与准确性。     

基于神经网络的多传感器融合技术研究

研究了基于神经网络的多传感器融合技术,并将其应用于自主吸尘机器人中.给出了神经网络传感器融合技术的基本原理,探索了改进的BP信息融合算法,使得改进后的算法在收敛速度上得到了很大的改善;介绍了传感器的监测系统和传感器特征的选择,构建了BP算法模型,并进行了仿真,得到了良好的实验结果.     

基于改进BP神经网络的预测模型及其应用

对BP神经网络的结构及其训练算法进行了研究,并针对传统BP算法的缺陷,提出了一种采用L—M算法的改进BP神经网络。在此基础上建立了基于改进BP神经网络的非线性系统预测模型,并通过具体的仿真及实践结果验证了改进BP神经网络的有效性。     

改进神经网络的传感器故障诊断与容错处理

为提高神经网络对霍尔传感器发生故障诊断率,设计了一种改进神经网络模型,该模型由反向传播(BP)神经网络并行组成,利用算法对各BP神经网络输出进行加权整合,进而得到误差更小的输出结果,并将改进神经网络模型应用于无刷直流电机霍尔传感器故障诊断系统中,利用无位置传感器系统实现霍尔传感器故障容错处理。仿真结果表明:改进神经网络故障诊断准确率达到96%,高于传统BP神经网络,且容错控制系统能够显著降低霍尔传感器故障对电机转速的影响,使电机能够在霍尔传感器故障时正常稳定运行。     

基于PSO-BP的无线传感器网络数据融合算法研究

为提高无线传感器网络(WSN)数据融合效率,减少网络的通信量以及降低传感网的能量消耗,提出一种基于粒子群优化BP神经网络的无线传感器网络数据融合算法;该算法将粒子群算法优化BP神经网络的权值和阈值后,与传感器网络分簇路由协议有机结合,将无线传感器网络中簇头和节点等同于BP神经网络里的神经元,利用优化后的BP神经网络有效地提取WSN数据融合原始数据之中的少量特征数据,之后把提取的特征数据发送到汇聚节点,进而提升数据融合效率,延长网络生存周期;仿真实验证明,与LEACH算法、BP神经网络和GABP算法相比,该算法可有效减少网络通信量,降低节点总能耗的15%,延长网络生存时间。     

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。     

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.