改进粒子群优化Takagi-Sugeno模糊径向基函数神经网络的非线性系统建模

针对复杂非线性系统建模的难点问题,提出了一种基于改进的粒子群优化算法（PSO)优化的T-S模糊径向基函数（RBF）神经网络的新型系统建模算法。该算法将T-S模糊模型良好的可解释性及RBF神经网络的自学习能力相结合,构成T-S模糊RBF神经网络用于系统建模,并采用动态调整惯性权重的改进的PSO算法结合递推最小二乘算法实现网络参数的优化调整。首先,利用所提算法进行了非线性多维函数的逼近仿真,仿真结果均方差（MSE）为0.00017,绝对值误差不大于0.04,逼近精度较高;又将该算法用于建立动态流量软测量模型,并进行了相关的实验研究,动态流量测量结果平均绝对误差小于0.15L/min,相对误差为1.97%,基本满足测量要求,并优于已有算法。上述仿真及实验研究结果表明,所提算法对于复杂非线性系统具有较高的建模精度和良好的自适应性。     

基于BP神经网络的电子设备故障诊断技术

故障诊断涉及模式分类与识别问题,神经网络对外界输入样本有很强的识别分类能力,能很好地实现非线性曲面的逼近.因此神经网络在设备故障诊断中能很好地得到应用,BP神经网络是目前最为广泛和成功的神经网络之一.介绍了BP神经网络在电子设备故障诊断技术中的应用,讨论了BP神经网络的算法和改进算法及其诊断过程,并对某型电台的故障诊断进行了MATLAB仿真.     

基于PID神经网络的非线性动态系统控制

基于PID神经网络的控制器可以完成变量的单输入-单输出非线性系统的任务.该控制器采用BP(误差反向传播)算法来修正连接权重值,通过在线训练和学习,使目标函数到达最优值.充分利用了BP神经网络算法逼近任意连续有界非线性函数的能力,显示了神经网络在解决非线性系统方面的潜能.为了达到控制的目的,和其他非线性建模技术相比较,PID神经网络有几个明确的优点和它独特的用法相一致.仿真结果表明,在对非线性动态系统控制时,基于PID神经网络的控制系统具有很强的灵活和高效性,能取得良好的控制效果.     

基于复合正交神经网络的自适应逆控制系统

目前，在自适应逆控制系统中常采用BP神经网络，而BP网络存在算法复杂、易陷入局部极小解等不足。而正交神经网络能克服BP网络的不足，但由于正交神经网络学习算法存在某些局限性，提出了一种复合正交神经网络，该正交网络结构与三层前向正交网络相同，不同的是正交网络的隐单元处理函数采用带参数的Sigmoid函数的复合正交函数，该神经网络算法简单，学习收敛速度快，并能对网络的函数参数进行优化，为非线性系统的动态建模提供了一种方法。仿真实验表明，网络在用于过程的自适应逆控制中具有很高的控制精度和自适应学习能力。该动态神经网络比其它神经网络具有更强的建模能力与学习适应性，有线性、非线性逼近精度高等优异特性，非常适合于实时控制系统。     

基于PSO-WNN的MEMS陀螺随机误差建模普适性分析

针对MEMS陀螺仪随机误差对系统导航精度影响以及现有建模方案存在个体普遍适用性问题,提出将粒子群优化算法(PSO)与小波神经网络(WNN)结合后对MEMS陀螺随机误差进行预测的建模方法,完成小波神经网络的构建。利用小波函数作为神经网络中隐含层的激励函数,同时将小波神经网络各层的连接权值作为粒子群优化算法中粒子的位置,使得建立的模型函数逼近能力更加灵活有效且增强其容错能力,同型号不同个体MEMS传感器建模补偿实验结果表明,论文提出的PSO-WNN误差建模方法预测的MEMS陀螺仪随机误差均值和标准差分别优于0.025°/s和0.13°/s,补偿后的MEMS陀螺Allan方差分析结果进一步验证了论文所提方法的可行性与普适性。     

一种小型惯性测量单元的精确标定技术

研究了一种基于MEMS陀螺和加速度计的惯性测量单元(IMU)的系统标定技术,建立了陀螺和加速度计的温度漂移和非线性误差模型,采用逐步线性回归法对以上模型进行了简化,并设计了补偿算法;实时补偿效果表明,在-40℃~60℃的温度变化范围内,惯性测量单元的零位偏值、偏值稳定性和非线性度都达到较高精度,这种误差标定方法可有效解决MEMS-IMU惯性器件误差的标定与补偿问题。     

基于PSO算法的WNN大包线增益调参控制律设计

提出了一种基于粒子群优化算法的小波神经网络大包线调参控制律设计方法.该方法用小波函数代替了Sigmoid函数作为激活函数.由于结合了小波变换良好的高频域时间精度、低频域频率精度的性质和神经网络的自学习功能,因而具有较强逼近非线性函数的能力.为了克服局部极小值问题并进一步提高对非线性函数逼近能力,利用粒子群优化算法对小波神经网络进行参数训练,并利用该网络实现了大包线增益调参.飞行仿真结果表明,所设计的小波神经网络增益调参控制器具有优良的控制性能,不仅能够保证平衡状态下的控制效果,而且在未训练的平衡状态下依然具有良好的控制性能,并且在存在20%的建模误差时,最大超调量仅为6 m,仅是使用常规增益调参方法的18%.     

控制增益符号未知的不确定非线性系统鲁棒自适应控制

针对一类控制增益函数及符号均未知的不确定非线性系统,基于反推滑模设计方法,提出一种鲁棒自适应神经网络控制方案.结合Nussbaum增益设计技术和神经网络逼近能力,取消了控制增益函数及符号已知的条件,应用积分型Lyapunov函数避免了控制器奇异性问题,并通过引入神经网络逼近误差和不确定干扰上界的自适应补偿项消除了建模误差和不确定干扰的影响.理论分析证明了闭环系统所有信号半全局一致终结有界,仿真结果验证了该方法的有效性.     

基于改进BP神经网络的函数逼近性能对比研究

为了正确反映实际应用中经常采用的6种典型BP神经网络的改进算法的非线性函数逼近能力,本文从数学角度详细阐述这6种典型BP神经网络的改进算法的学习过程,简要地介绍MATLAB工具箱中设计BP网络的训练函数,最后在MATLAB环境下设计具体的网络来对指定的非线性函数进行逼近实验,并对这6种典型BP神经网络的改进算法的性能差异进行对比。仿真结果表明,对于中小规模网络而言,LM优化算法逼近性能最佳,其次是拟牛顿算法、共轭梯度法、弹性BP算法、自适应学习速率算法和动量BP算法。     

洪泽湖水位预测模型的研究

水位预测是进行洪水监测的规则非线性函数关系,不易使用某个函数进行逼近.采用了BP神经网络对历年的水文信息进行学习、建模,实现了对这种不规则函数的拟合,并支持在线学习及适时调整.另外,使用改进的粒子群优化算法(PSO)对常规的BP网络进行训练.实验结果表明使用由改进的粒子群优化算法进行训练的BP神经网络进行的水位预测的精度有显著提高,并且在训练过程中尽可能地避免收敛于局部最优值.     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and     

Editorial:Brain-machine interface(BMI) and cyborg intelligence

正Brain-machine interfaces(BMIs)aim at building a direct communication pathway between the brain and an external device,and represent an area of research where significant progress has been made during the past decade.Based on BMIs,mind information can be read out by neural signals to control     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate     

SCIENCE CHINA Information Sciences SUBJECT INDEX TO VOLUME 57(2014)

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Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate