基于蚁群算法的多维有约束函数优化研究*

利用蚁群算法的基本原理,将多维有约束的优化问题通过罚惩因子方式转换为统一的多变量目标函数形式,并将所有独立变量分成不同的等份区域,以蚂蚁走过每一变量的一个区域并访问完所有变量所构成的构造图作为优化问题的可行解,获得这一可行解的过程即为蚁群算法的粗搜索;再将粗搜索所获得的解执行遗传交叉及变异操作,从而构建另一种精搜索蚁群算法以获得更精确的全局优化解。给出了基于蚁群算法的多维有约束函数优化的具体算法。通过其他三种优化方法及本文方法对行星轮系优化设计的对比求解,验证了该优化方法的高效性及准确性。     

连续空间优化问题的自适应蚁群系统算法

蚁群算法是进化计算中一种新型优化算法,其基本算法用于求解排序类型的组合优化问题本文提出一种用于连续空间优化问题求解的蚁群算法,采用了新的基于目标函数值的启发式信息素分配算法,以及搜索过程中最优解的筛选方法.根据目标函数来自适应调整蚂蚁的路径搜索行为,从而保证算法快速找到全局最优解.一个多极值点的连续优化问题求解实例证明了该方法的有效性     

基于改进蚁群算法的模糊控制器优化设计

研究控制器优化问题,由于模糊控制系统参数无法同时优化,使得系统选择参数困难,使系统控制效果存在一定的缺陷,安全性和可靠性降低。为解决上述问题,提出了一种多种群进化蚁群算法对模糊控制器优化设计。采用懒蚂蚁效应的改进蚁群算法进行优化,在传统蚁群算法的基础上,采用多个种群并行,对算法的初始化、路径构建以及信息素更新改进,并引入到模糊控制器的隶属函数、模糊规则的优化搜索中,搜索出适应于不同控制阶段的模糊控制器参数及控制规则,并进行仿真。仿真结果证明了改进算法对模糊控制器的参数具有良好的搜索速度和精度,使系统有很强的鲁棒性。     

具有时延约束网络路由问题的自适应蚁群优化算法

高速多媒体网络中的路由问题是有QoS约束的路由问题,满足一个或多个约束的路由问题是NP-完全问题,其中,具有时间延迟约束的QoS路由问题是一个极具代表性的问题。本文给出了一种求解具有时间延迟约束的QoS路由问题的自适应蚁群算法。该算法在种群中采用基于目标函数值的启发式信息素分配策略和根据目标函数自动调整蚂蚁搜索路径的行为。比一般蚁群算法具有更强的鲁棒性和全局优化能力。理论分析和仿真实验表明,该算法是有效的网络QoS路由算法。     

基于多层蚁群算法的变论域模糊控制

针对模糊控制器控制精度不高、自适应能力有限等问题,提出一种变论域自适应模糊控制方式.首先在对离散蚁群算法改进的基础上,提出用于连续域寻优的多层蚁群算法.其通过将解空间分成有限网格,并且算法在迭代过程中采用三个阶段的搜索策略,每个阶段采用异构搜索机制.然后根据系统性能利用改进算法动态调整伸缩因子,从而构成基于多层蚁群算法的变论域自适应模糊控制器.最后将此控制器用于中厚板液压位置伺服系统中.仿真结果表明,采用自适应模糊控制器的伺服系统收敛速度明显加快,此控制策略在适应能力与鲁棒性好于其它控制方式.     

基于混沌遗传算法的模糊CMAC控制

分析CMAC神经网络和模糊控制的特性,给出了一种能反映人脑认知的模糊性和连续性的模糊CMAC神经网络控制器,该控制器采用高斯函数作为模糊隶属函数,利用神经网络实现模糊推理并可对隶属函数进行实时调整,从而使其具有学习和自适应能力;针对BP算法易陷入局部极值点的缺点和简单遗传算法局部搜索能力差的不足,提出了一种混合学习算法,即首先利用混沌遗传算法全局搜索的特点来离线优化神经网络的参数,再利用BP算法较强的局部搜索能力对网络参数进行在线调整;仿真结果表明了该方法的可行性和有效性.     

基于蚁群聚类的自适应神经网络算法

针对模糊神经网络结构辨识问题,提出了一种基于蚁群聚类的自适应神经网络算法。利用蚁群聚类算法确定模糊神经网络的初始结构,在网络的学习过程中,采用误差反向传播学习算法对网络的参数和结构进行优化,达到自适应调整权值参数和结构的目的。最后,针对非线性函数遥近问题进行了验证。通过仿真试验证明该方法取得了很好的结果,系统的逼近精度明显提高,而且网络的自适应能力强,并可以将其有效地用于模糊建模和控制问题的求解。     

基于并行多种群自适应蚁群算法的聚类分析

数据聚类是数据挖掘中的一个重要课题。聚类问题可以归结为一个优化问题。蚁群算法作为一种鲁棒性很强的优化算法具有很强的全局优化能力。该文给出了一种并行多种群自适应蚁群算法。该算法采用多种群并行搜索,并在种群中采用基于目标函数值的启发式信息素分配策略和根据目标函数自动调整蚂蚁搜索路径的行为。理论分析和仿真实验表明,该算法是非常有效的。     

一类Takagi-Sugeno模糊控制器的自适应遗传优化设计

提出了一类Takagi-Sugeno模糊控制器的自适应遗传优化设计方法。采用实数编码方式,并由自适应交叉和变异概率来控制遗传操作,有效地提高了参数优化的精度和算法的寻优效率。在优化过程中引入对称性参数约束条件,大大减小了算法的搜索空间。将该算法用于倒立摆T-S模糊控制器的设计,实现了控制器参数的快速自动整定。仿真结果表明,获得的T-S模糊控制器具有优良的性能。     

基于自适应蚁群算法的多受限网络QoS路由优化

高速多媒体网络中的路由问题是有QoS约束的路由问题，多受限的路由问题是一个NP-完全问题。该文提出了一种解决多受限QoS路由问题的自适应蚁群算法。该算法采用基于目标函数值的信息素分配策略和根据目标函数值自适应调整蚂蚁的搜索行为，从而保证搜索的快速有效性，使多受限QoS路由优化问题得到很好地解决。     

Call for Papers The 6^th International Conference on Grid and Cooperative Computing

Recent years have seen rapid advances in various grid-related technologies, middleware, and applications. The GCC conference has become one of the largest scientific events worldwide in grid and cooperative computing. The 6th international conference on grid and cooperative computing (GCC2007) Sponsored by China Computer Federation (CCF),Institute of Computing Technology, Chinese Academy of Sciences (ICT) and Xinjiang University ,and in Cooperation with IEEE Computer Soceity ,is to be held from August 16 to 18, 2007 in Urumchi, Xinjiang, China.     

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.     

法律信息库系统

本文分析了法律数据库的结构和特点，介绍了采用面向对象设计方法和超文本数据库技术开发和实现法律信息库系统将作为重要网络资源之一为不同用户进行法律咨询服务。     

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.     

International Journal of Automation and Computing Table of Contents

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Information for authors

正SCIENCE CHINA Information Sciences(Sci China Inf Sci),cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China,and published by Science China Press,is committed to publishing highquality,original results of both basic and applied research in all areas of information sciences,including computer science and technology;systems science,control science and engineering(published in Issues with odd numbers);information and communication engineering;electronic science and technology(published in Issues with even numbers).Sci China Inf Sci is published monthly in both print and electronic forms.It is indexed by Academic OneFile,Astrophysics Data System(ADS),CSA,Cabells,Current Contents/Engineering,Computing and Technology,DBLP,Digital Mathematics Registry,Earthquake Engineering Abstracts,Engineering Index,Engineered Materials Abstracts,Gale,Google,INSPEC,Journal Citation Reports/Science Edition,Mathematical Reviews,OCLC,ProQuest,SCOPUS,Science Citation Index Expanded,Summon by Serial Solutions,VINITI,Zentralblatt MATH.     

Erratum to: Fast global kernel fuzzy c-means clustering algorithm for consonant/vowel segmentation of speech signal

正Erratum to:J Zhejiang Univ-Sci C(ComputElectron)2014 15(7):551-563doi:10.1631/jzus.C1300320The original version of this article unfortunately contained mistakes.Algorithm 6 should be as follows:Algorithm 6 FGKFCM-F clustering Input:(1)X={x_1,x_2,…,x_N},,x_iR~d,i=1,2,…,N,the dataset;(2)C,1C≤N,the number of clusters;(3)ε0,the stopping criterion;     

Journal of Zhejiang University-SCIENCE C (Computers & Electronics) Total contents

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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.