基于情感智能的球磨机系统自适应辨识算法

在球磨机优化控制的研究中,球磨机系统为高耗能系统.由于球磨机系统具有非线性和时变性,使得其模型难以实现准确性要求.针对上述问题,提出采用大脑情感学习模型(Brain Emotional Learning,BEL)的球磨机系统在线辨识算法.分别建立了大脑情感学习模型的球磨机系统正向模型和逆模型辨识结构,通过调整BEL权值使得BEL输出与球磨机系统输出或输入达到一致.仿真结果表明,改进方法具有算法简单、鲁棒性强和模型辨识精度高的特点.     

基于菌群优化算法的非线性系统模型参数辨识

非线性系统模型参数估计一直是自动控制领域的研究热点。针对非线性系统,结合菌群优化(BSFO)算法的特点,提出了一种新型的非线性系统模型参数辨识方法。通过将待辨识参数设置为群体细菌在参数空间的位置,并模拟细菌群体觅食的动态行为来实现对系统参数的辨识,有效地提高了参数辨识的精度和效率。通过对重油热解三集总模型进行了仿真研究,得到了较为精确的过程模型,模型输出与实际输出基本一致。仿真结果表明,菌群优化算法为非线性系统模型参数估计提供了一种有效的途径。     

基于樽海鞘群算法的床温多变量系统辨识研究

针对热工系统具有多输入多输出的特点,介绍将多输入多输出系统简化为多个多输入单输出系统的具体过程。利用机组的实际运行数据,建立在50%负荷运行工况下,以给煤量、煤泥量和一次风量为输入,以床温和主蒸汽压力为输出的多变量系统模型。为提高模型参数辨识的精度,采用樽海鞘群算法(SSA)对多变量系统的模型参数进行寻优。该算法采用一种新的群体更新模型,算法流程简单。仿真结果表明,相比于传统粒子群算法(PSO),樽海鞘群算法运算速度明显提高,可以获到更优的辨识模型。     

基于引力搜索算法的造纸过程模型辨识

造纸过程是一个多输入多输出的过程,造纸过程的模型辨识具有重要的研究意义。建立了造纸过程的多输入多输出模型,采用引力搜索算法(GSA)对造纸过程的模型进行参数辨识,并将预测模型的预测输出与实际模型的输出作对比。同时,论文使用广义增广随机梯度算法(GESG)对该造纸过程的模型进行辨识,并将两种算法的辨识效果进行对比。结果表明,GSA在造纸过程的辨识方面具有较高的辨识精度,预测模型的输出与系统输出较为吻合。相比于GESG算法,GSA具有收敛速度快、辨识精度高等优点。在不同的噪声方差影响下,GSA也能取得较好的辨识效果。该算法对造纸过程的参数辨识具有一定的可行性。     

广义预测控制的直接算法

采用三个辨识器分别辨识开环系统、闭环系统和控制器的参数,利用开环系统参数计算预测输出和参考轨迹,通过辨识闭环系统参数得到广义输出,用于辨识控制器的参数,并给出一种广义预测控制的直接算法。仿真结果表明该算法是有效可行的。     

应用改进粒子群算法辨识Hammerstein模型

研究非线性系统辨识问题.针对非线性系统中单输入单输出Hammerstein模型,由于传统辨识方法对Hammerstein模型中非线性部分具有不易辨识的缺陷,造成辨识精度低、辨识效果差等问题.为此,在基本粒子群算法的基础上,提出了一种带有收缩因子的改进的粒子群算法对非线性系统进行辨识的方法,可将参数辨识问题转换为参数空间上的函数优化问题,然后利用粒子群算法的并行搜索能力进行参数寻优.通过MATLAB软件进行仿真,并与基本粒子群算法进行比较,结果表明,利用改进算法不仅提高了辨识精度而且获得了良好的辨识效果,从而验证了算法的有效性和可行性.     

基于辅助模型正交匹配追踪的多输入系统迭代辨识算法

针对含有未知时滞的多输入输出误差系统的时滞与参数辨识问题,提出一种基于辅助模型的正交匹配追踪迭代算法.首先,由于各输入通道的时滞未知,通过设定输入回归长度,对系统模型进行过参数化,得到一个高维的辨识模型,且辨识模型中参数向量为稀疏向量;然后,基于辅助模型思想和正交匹配追踪算法,在每次迭代过程中,对参数向量和辅助模型的输出进行交互估计,即利用正交匹配追踪算法获得参数向量的估计,再利用参数估计值计算辅助模型的输出,并用辅助模型的输出值代替信息向量中的不可测信息项以更新参数估计;最后,根据参数向量的稀疏特征,获得系统的时滞估计.所提出算法可以利用少量的采样数据信息同时获得系统参数和时滞的估计值.仿真结果表明了所提出算法的有效性.     

水下机器人参数辨识的量子粒子群算法

水下机器人动力学模型参数辨识是水下机器人运动状态控制、路径跟踪、状态监测、故障诊断及容错系统开发的基础,是水下机器人研究的核心内容之一.针对Falcon开架缆控水下机器人的动力学模型,将量子粒子群优化算法引入到水下机器人动力学模型参数辨识之中,提出基于量子粒子群优化算法(Quantum-behaved PSO,QPSO)的水下机器人动力学模型参数辨识,并将其辨识结果与粒子群优化算法(Particle Swarm Optimization,PSO)及遗传算法(GA)的辨识结果进行比较.仿真结果表明应用QPSO算法的参数辨识结果明显优于其它对比方法,说明了算法的有效性与合理性.     

一种新型非线性系统模型参数辨识方法

关于非线性自动控制系统优化问题,为解决复杂非线性系统的辨识问题,提出了一种基于菌群优化算法的非线性系统辨识方法.结合菌群优化算法的特点,通过将待辨识参数设置为群体细菌在参数空间的位置,并利用细菌群体觅食的动态行为来实现对系统参数的辨识,有效地提高了参数辨识的精度和效率.通过对重油热解三集总模型进行了仿真研究,得到了较为精确的过程模型,模型输出与实际输出基本一致.仿真结果表明:菌群优化算法为非线性系统模型参数估计提供了一种有效的途径.     

基于平淡粒子滤波的自组织模糊神经网络算法

提出一种基于平淡粒子滤波(UPF)的自组织模糊神经网络(SOFNN)训练算法--UPF-SOFNN。分析了基于误差下降率的模糊规则增删策略和神经元增加和删除准则,建立了以隶属函数宽度参数为状态,以理想输出为量测的动力学模型,并利用UPF对神经元参数进行学习。分别以非线性系统函数逼近和系统辨识为例,对UPF-SOFNN算法进行了仿真验证,表明UPF-SOFNN算法具有更紧凑的结构和较强的泛化性能。     

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.