非对称非线性平滑转换的广义自回归条件异方差算法的碳价格均值回归检验

本文利用非对称非线性平滑转换的广义自回归条件异方差(ANST–GARCH)算法对欧盟碳排放权价格均值回归特征进行了检验,研究表明:1)在欧盟碳交易市场3个阶段的发展进程中,第Ⅰ阶段欧盟排放权配额(EUA)价格序列变动服从均值回避,第Ⅱ, Ⅲ阶段均具有非对称均值回归特征; 2)经过风险调整后的欧盟碳配额价格序列仍然具有非对称性均值回归特征,负的均值回归速度和幅度明显大于正的均值回归速度和振幅; 3)均值回归与投资者对信息的过度反应有关,与时变理性预期无关.具体而言,第Ⅰ阶段拒绝过度反应假设,接受时变理性预期假设;第Ⅱ,Ⅲ阶段接受过度反应假设,拒绝时变理性预期假设.     

一种基于多重分形的软件衰退分析方法

为了提高软件衰退预测的精度,采用了多重分形分析方法,以系统资源参数时间序列为研究对象,提出了一种定性和定量相结合的分析方法,用以研究其波动规律.定性分析阶段,借鉴分形理论分析影响软件性能的系统资源参数,揭示参数的波动具有分形特性;且其多重分形谱特征能刻画系统运行过程中随时间变化的情况.定量预测阶段,提出了一种多维的Hlder指数计算方法,用于计算多个资源参数序列的Hlder指数,并采用自回归移动平均模型(ARMA)预测Hlder指数.最后进行了实证分析,结果表明,该方法具有较好的定性分析和定量预测能力.     

基于多重分形的VBR视频流量多步预测方法

视频流量的实时预测是进行网络资源优化和端到端QoS策略设计的重要前提.然而,目前基于短相关(SRD)的预测模型并不能对非平稳且具有长相关(LRD)和分形特性的视频流量进行有效的预测.分析发现,通过多重分形尺度间系数的相关性,可以把难以直接预测的LRD流量序列转化为可以用SRD模型预测的短相关序列组.基于多重分形的预测算法合理地利用了原始序列的LRD信息,具有很好的多步预测性能.     

基于LFSN和小波变换的业务流预测算法

针对实际业务流预测精度偏低的问题,结合线性分形稳定运动(LFSM)模型和小波变换提出一种新的业务流预测算法(SPWL)。定义线性分形稳定噪声(LFSN)分布特征,利用离散傅里叶变换产生满足LFSN过程的数列,并给出实际业务流数据拟合方法。通过小波变换降低实际业务流的突发特性,同时融合LFSM模型的预测结果提高实际业务流的预测精度。基于NS2和Matlab进行仿真实验,结果表明,与FARIMA算法相比,SPWL算法预测精度较高,其预测误差仅为12.83%。     

基于小波变换的网络流量预测模型

目前研究发现实际网络流量具有明显的分形特性,流量的多重分形特性对网络性能有着非常重要的影响,有必要建立一个基于多重分形特性的可以同时预报长相关和短相关特性的实际网络业务模型。利用AR, ARMA等模型对短相关数据能较好地预测而对长相关数据预测精度不高的特点,并结合小波变换能够去除实际数据相关性,建立新的预测模型,使其对长相关数据同样具有比较高的预测精度。改进后的模型克服了FARIMA模型计算量比较大的缺点,保持了算法的简单性。     

网络业务多重分形特性研究

聚集网络业务的多重分形特性既能考查多尺度下业务的突发性,又能描述突发性相对于时间的变化,是网络业务最显著的统计特性之一.使用网络流量的联合多重分形(JMF)模型 [7]对实际数据进行分析及参数估计,检测网络业务多重分形结构,并产生理论多重分形流量.将JMF模型理论流量、基于自相似特性的分形布朗运动(FBM)模型的理论流量和实际测量流量作为OPNET仿真驱动,进行网络性能仿真.仿真结果显示由JMF模型产生的理论流量与实际测量流量的性能更为接近,进一步验证了网络业务的多重分形特性.     

碳排放权价格均值回归的周期及振幅

本文运用谱估计技术分析了欧盟碳排放权价格均值回归周期、幅度及其与WTI,PMI之间的耦合关系.研究表明:1)EUA现货价格具有显著的均值回归周期振荡特征,周期约在15.5个月与3个月之间;振幅约在-2.298到4.823之间;2)EUA现货价格均值回归与WTI原油价格指数的耦合周期在3个月到12个月之间,耦合振幅在0.1958到0.8843之间,与PMI指数耦合周期约为4个月到11个月之间.耦合振幅在0.1652到2.134之间;3)在所有耦合周期模态下,耦合周期越长,耦合振幅越小.     

基于混合人工神经网络的电力市场短期电价研究与分析

由于电力市场价格的不确定性,供需侧管理在电力市场中遇到了许多困难。电力供应商可以通过了解电力市场价格变化的信息,在短期预测其合理报价时获得更多优势。因此,近年来,电力市场对价格预测的研究变得更加重要。根据预测框架,预测技术可分为三类,即统计模型、时间序列方法和基于人工智能(AI)的方法。因此,为解决上述问题,提出一种基于混合人工神经网络的短期电价预测混合方法。同时,本研究开发了一种基于互信息(MI)和神经网络(NN)相结合的特征选择技术,用于选择输入变量子集,这些子集对电价预测具有重要影响。通过结合人工协同搜索算法(ACS)和人工神经网络(ANN)进行,进一步提高了预测的精度。通过比较所提出的混合预测方法与混合SVM和混合ANN方法的相关性和精度,并通过粒子群优化(PSO)CSA算法对混合SVM和混合ANN方法的参数进行了优化。开发的ANN-ACS模型在电力市场具有鲁棒性。在电价预测的情况下,它提供了比其他AI方法更高的预测精度和简单性,在冬季、春季、夏季和秋季的MAPE值分别为4.58%、1.2%、2.62%和3.79%。     

基于经验模式分解和极限学习机的铀资源价格预测方法

针对国际铀资源价格预测问题, 提出一种基于经验模式分解(EMD)、相空间重构(PSR) 和极限学习机(ELM) 的非线性组合预测方法. 首先通过EMD分解, 将原始价格序列分解为若干固有模态分量(IMF), 按频率高低将各IMF 分组叠加成3 个新序列; 然后在重构相空间的基础上构建不同的ELM模型, 分别对各IMF 序列进行预测; 最后对预测结果进行合成. 将该方法应用于实际铀资源价格预测, 并与径向基神经网络(RBF) 方法及单独ELM方法进行比较, 仿真结果表明该方法预测精度有明显的提高.

     

CVaR测度下考虑碳排放的生产策略研究

为了解决低碳经济下生产商考虑碳排放权限制的生产策略问题,考虑碳排放权主要来自于政府配额、市场交易和净化减排处理三种方式,建立了随机需求和政府配额限制下基于CVaR测度的生产商生产优化决策模型,分析了生产商获取政府配额以外碳排放权的优先选择市场交易与净化处理方式的决策条件,与生产商净化处理成本、净化处理水平和碳排放权市场交易价格相关,与生产商的风险规避水平无关,并得到了生产商在碳排放权限额下的最优生产策略。最后通过算例分析说明了模型的有效性以及模型参数对生产商最优化决策的影响。     

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