基于ANFIS模型的烟气含氧量建模和预测

针对电厂热工测量参数难以进行有效预测的问题,提出一种基于ANFIS模型的烟气含氧量建模和预测方法.基于自适应神经模糊推理系统(ANFIS)学习能力与泛化能力均较强的优点,建立软测量预报模型,借助某电厂循环流化床锅炉烟气含氧量实测数据进行仿真,结果表明,基于ANFIS的自适应预测模型,具有良好的预报能力,具有较高的预报精度和鲁棒性,可以较好地解决电厂烟气含氧量预测问题,对于实现锅炉燃烧系统的优化运行和预测控制具有一定的价值.     

减法聚类-ANFIS在网络故障诊断的应用研究

提出了一种基于减法聚类-自适应模糊神经网络（ANFIS）的网络故障诊断建模方法。减法聚类算法生成初始模糊推理系统,ANFIS建立网络故障诊断原始模型,应用混合算法对模糊规则的参数进行训练并建立最终的模型。仿真实验表明基于减法聚类-ANFIS的建模方法是有效的;通过仿真结果比较,减法聚类-ANFIS的网络故障诊断能力及收敛速度均优于BP神经网络,更适合作为网络故障诊断模型。     

一种基于ANFIS的ABR拥塞控制

由于ATM网络环境的复杂性、多变性,用常规的数学模型对网络模型、可用带宽的获取以及控制器设计的描述具有很大的局限性,因此论文提出了一种基于自适应模糊推理系统(AdaptiveNeuralFuzzyInferenceSystems,ANFIS)的ABR业务拥塞控制方法,该方法结合模糊推理系统的规则结构化及神经网络强泛化能力的优点,克服了模糊推理模型的偶然性和神经网络收敛速度慢、训练时间过程长等缺点。仿真结果表明使用ANFIS进行拥塞控制的可行性,增加了系统稳定性并减小了信元丢失率。     

基于神经网络的鸟撞预测模型应用研究

通过对某机场地理环境、生境、鸟类及鸟类活动、鸟情信息进行综合分析,在收集、规范、完善鸟情数据集的基础上,文中给出了鸟情数据预处理方法,提出了一种基于神经网络的鸟撞预测模型,确定了鸟撞预测模型输入、输出参数,并分别采用BP神经网络和径向基网络(RBF)两种方式建立预测模型.运用Matlab对两个预测模型性能进行仿真实验,仿真实验结果表明BP神经网络比RBF神经网络预测具有更高精度、更小误差.最后,通过机场实际观察数据对训练好的鸟撞模型做仿真预测,结果进一步验证了BP神经网络鸟撞预测模型具有很好的预测效果     

改进的GPC在基于以太网的网络控制系统时延中的应用

针对基于以太网的网络控制系统(NCS)具有随机时延的特性,提出了将广义预测控制应用于网络控制系统中.为克服模型失配和系统不确定性的影响,基于BP神经网络建立一个误差的预测模型,用误差预测值对输出预测值进行补偿,构建了带误差补偿的广义预测控制算法.实验仿真验证了带误差补偿的广义预测控制在模型失配时具有更好的控制效果.     

基于遗传算法的模糊神经网络公交到站时间预测模型研究

公交到站时间的预测受到诸多因素的影响,各种因素对预测准确度不可度量,很难采用传统数学模型进行建模解决。采用基于遗传算法的模糊神经网络模型对公交到站时间进行预测,该模型将遗传算法和模糊推理系统融入多层前馈神经网络中,并通过模糊规则的隶属度进行初始化与更新网络各个参数初始值,同时利用多子群自适应遗传算法进行宏观搜索,提高整个网络的寻优能力。模型以成都市某线路公交运行时间预测为例对其进行了模拟仿真,仿真结果表明基于遗传算法的模糊神经网络公交到站时间预测模型具有较高的准确性与可靠性。     

混沌时间序列的自适应变异差分进化ANFIS预测

提出了一种基于自适应变异差分进化（AMDE）算法的ANFIS模型对混沌时间序列进行预测的方法,该方法采用自适应变异差分进化算法和最小二乘法相结合的混合学习算法对ANFIS网络结构参数进行优化设计,利用差分进化算法的全局寻优能力对ANFIS网络前件参数进行优化,而网络的结论参数采用最小二乘法优化,混合学习算法提高了网络参数辨识的收敛速度和系统的全局收敛性,仿真实验结果表明了该方法的有效性。     

基于ANFIS的机器人系统建模的研究

针对机器人这种不确定性的复杂非线性系统很难建立其精确的数学模型这一问题,提出一种基于自适应神经模糊推理(ANFIS)的方法对机器人系统进行建模.此方法将模糊推理和神经网络的学习能力有机地结合起来,并利用神经网络的学习机制自动地从输入输出数据中提取规则.建模过程中为了给ANFIS赋予一个合适的初始状态,选用减法聚类对输入数据进行处理.ANFIS网络的所有参数采用混合算法进行调节,即前提参数采用误差反向传播法,结论参数采用最小二乘法.最后在Matlab中对二自由度机器人进行仿真研究,仿真结果表明该方法模型结构简单,建模速度快,辨识精度高,同时也验证了该方法的有效性,为进一步实现机器人鲁棒自适应控制打下基础.     

基于灰色G(1,1)和小波神经网络的预测模型及应用

将灰色系统、小波分析和三层BP神经网络各自优点集于一身建立了基于灰色G(1,1)和小波神经网络的预测模型,大幅度提高了模型的预测精度和可靠性。选用我国自1994年至2006年狂犬病发病率统计数据,用灰色GM(1,1)模型对历年的疾病发病人数进行建模,将拟合值做小波神经网络的输入进行二次拟合和预测。实验结果及仿真验证表明,本文模型预测效果远优于单一的灰色模型预测。     

基于遗传算法优化小波神经网络的短期天然气负荷预测

天然气负荷预测对于燃气经营企业尤其重要,对保证天然气管网的用气量、优化管网的调度具有重要意义.传统的天然气预测模型预测精度低、模型泛化程度低.为了克服模型缺陷,提出了一种基于遗传算法优化小波神经网络的天然气负荷预测模型.通过遗传算法对小波神经网络的阈值以及网络连接权值等参数进行优化,从而建立预测效果最好的模型,通过企业提供的历史门站数据对预测模型进行验证.仿真结果表明,使用遗传算法优化网络参数的小波神经网络提高了模型的预测精度,具有一定的工程应用价值.     

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。