淬火炉温度的模糊优化控制

针对模压锻件淬火炉温度具有非线性、强耦合、长时迟延的特点。建立了它的温度模糊智能控制系统。将温度超调量、上升时间和稳态误差的加权和作为目标函数、遗传算法优化隶属函数参数和模糊推理规则。实验结果表明。控制方法能获得满意的控制效果。温度最大超调量小于4℃。保温阶段温度波动小于2℃。     

一种用模糊—神经技术建造专家系统的方法

本文提出了一种用模糊－神经技术建造专家系统的方法。从领域专家处获取的知识是以模糊规则和隶属函数的形式表示的。根据本文提出的方法，首先将模糊规则和隶属函数用神经网络表示出来（导入）；生成的神经网络用于实现模糊推理，然后利用修改的反传算法训练神经网络，从而提高系统的精度，修改隶属函数，求精模糊规则；最后从神经网络中提取隶属函数和模糊规则（导入），帮助解释神经网络的内部表示和操作，利用本文所提出的方法建     

基于自适应神经网络模糊推理的负荷预测

针对中长期负荷预测,本文将模糊理论与神经网络相结合,提出了基于高木-关野自适应神经网络模糊推理系统的中长期负荷预测模型.该模型采取神经网络技术对模糊信息进行处理.使得模糊推理系统的模糊规则和模糊隶属度函数能通过学习功能自动生成,从而有效地解决了模糊理论中必须根据专家经验人为制定规则和隶属度函数的瓶颈及采用神经网络所获得的输入/输出关系不易被人接受的问题;并以湖南省安乡县经济发展指标和全社会用电量为基础数据,通过高木--关野自适应神经网络模糊推理系统对安乡县预测年份全社会用电量水平的进行预测分析.算例表明,该推理系统计算快捷.准确性高,在电网规划中长期负荷预测中有较强的实用价值.     

一种用模糊－神经技术建造专家系统的方法

本文提出了一种用模糊－神经技术建造专家系统的方法（ＦＮＴ方法）。从领域专家处获取的知识是以模糊规则和隶属函数的形式表示的。根据本文提出的方法，首先将模糊规则和隶属函数用神经网络表示出来（导入）；生成的神经网络用于实现模糊推理，然后利用修改的反传算法训练神经网络，从而提高系统的精度，修改隶属函数，求精模糊规则；最后从神经网络中提取隶属函数和模糊规则（导出），帮助解释神经网络的内部表示和操作。利用本文所提出的方法建造的系统可实现快速的无匹配模糊推理，并具有较强的学习能力。     

基于FNN与GA相融合的数据挖掘方法研究

模糊神经网络即具有输入信号是模糊量的神经网络,是模糊系统与神经网络相结合的产物,汇聚了二者的优点;遗传算法是一种自适应全局优化概率搜索算法。研究了基于模糊神经网络与遗传算法相融合的一种算法,在应用模糊神经网络进行数据挖掘前,应用遗传算法完成隶属函数的训练,以便更好地进行模糊神经网络学习;经过模糊神经网络学习后,提取相关规则,再次应用遗传算法,进行规则剪枝,提高数据挖掘效率。实验表明,与传统方法相比,该方法能够更快速、更加准确地进行数据挖掘,提取更精确的推理规则。     

基于FNN与GA相融合的数据挖掘方法研究

模糊神经网络即具有输入信号是模糊量的神经网络,是模糊系统与神经网络相结合的产物,汇聚了二者的优点;遗传算法是一种自适应全局优化概率搜索算法.研究了基于模糊神经网络与遗传算法相融合的一种算法,在应用模糊神经网络进行数据挖掘前,应用遗传算法完成隶属函数的训练,以便更好地进行模糊神经网络学习;经过模糊神经网络学习后,提取相关规则,再次应用遗传算法,进行规则剪枝,提高数据挖掘效率.实验表明,与传统方法相比,该方法能够更快速、更加准确地进行数据挖掘,提取更精确的推理规则.     

三级倒立摆的加权变量模糊神经网络控制

为了提高三级倒立摆系统控制的响应速度和稳定性,在设计Mamdani型摸糊推理规则控制器控制倒立摆系统稳定的基础上,设计了一种更有效率的基于Sugeno型模糊推理规则的模糊神经网络控制器。该控制器使用BP神经网络和最小二乘法的混合算法进行参数训练,能够准确归纳输入输出量的模糊隶属度函数和模糊逻辑规则。通过与Mamdani型控制器的仿真对比,表明该Sugeno型模糊神经网络控制器对三级倒立摆系统的控制具有良好的稳定性和快速性,以及较高的控制精度。     

K-聚类的模糊神经网络对DO的控制研究

运用一种基于K-聚类算法的模糊径向基函数（RBF）神经网络对污水处理中的溶解氧质量浓度进行控制,该方法结合了模糊控制的推理能力强与神经网络学习能力强的特点,将模糊控制、RBF神经网络以及K-聚类学习算法相结合以在线调整隶属函数,优化控制规则。通过对阶跃输入仿真分析,其结果表明基于RBF的模糊神经网络控制器具有良好的动态性能、较强的鲁棒性和抗干扰能力,使其快速、准确地达到期望水平。     

基于Sugeno型神经模糊系统的交通流状态预测算法

从交通流状态的模糊特性出发,设计基于Sugeno型神经模糊系统的交通流状态预测算法.选择交通流状态的影响指标作为模糊推理系统的输入、交通流状态作为输出;据经验对输入、输出划分模糊子集,给出相应的隶属度函数并制定模糊规则;建立具有5层结构的神经模糊推理系统,利用神经网络优化调整模糊推理系统的隶属度函数和模糊规则.仿真实验表明,神经网络可直接优化模糊推理系统的隶属度函数,通过对连接权值的训练间接优化模糊规则,故Sugeno型神经模糊系统相比常规模糊系统具有更好的交通流状态预测性能.     

基于B样条隶属函数的模糊推理系统

隶属函数和推理规则的确定是模糊推理的难点。通过研究模糊推理过程和B样条函数的特性,对应用B样条函数拟合模糊隶属函数进行推理的方法进行改进。通过对误差极值点、曲率极值点的计算和筛选,得到B样条函数的型值点。反算求得控制点之后,通过自适应增加控制点对曲线进行调整,增加曲线对隶属函数的拟合度,解决了B样条函数对隶属函数的拟合问题。建立B样条推理规则,构造实现了B样条推理系统,并求出该系统的最终结果为B样条超曲面。最后,通过实验验证了该方法的有效性和可行性。     

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.