基于Petri网化简技术的工作流模型正确性研究

为了更有效地对工作流模型进行分析验证,提出了一种基于Petri网化简技术的工作流模型正确性验证方法。在对各种工作流模型验证技术深入研究的基础上,通过对非自由选择网结构活性和有界性的分析,给出了针对Petri网中非自由选择部分的分析方法。在保持活性和有界性的前提下,给出了将活的且有界的非自由选择部分转化为自由选择部分的转化方法,从而将非自由选择的Petri网验证问题转化为自由选择Petri网的验证问题。通过一个例子说明了如何使用该文提出的方法来验证模型的正确性。

UML活动图模型正确性诊断方法

UML活动图的正确性决定了业务流程的正确执行,为此,提出一种UML活动图模型的正确性诊断方法。将模型分解后,对子模型进行模型验证,并对验证错误的子模型进行模型诊断,得到诊断结果。在质量管理过程实例中的应用结果表明,该方法能减小模型空间,减少诊断次数,准确锁定错误,有效地对模型的正确性进行诊断。

团队心智模型相似性与正确性对团队创造力的影响

现代组织越来越依赖团队进行创造与创新活动,团队创造力成为理论与实践共同关注的热点问题。最新理论指出,与个体类似,团队也是信息加工者,团队决策实质上也是信息搜寻、编码、存储和提取的认知加工过程。从团队认知角度开展研究是团队创造力领域的新方向。鉴于此,本研究从团队认知的角度出发,探讨共享心智模型与团队创造力之间的关系。基于80个信息平台运行维护团队的数据,研究结果表明,心智模型的相似性与正确性均能影响团队创造力,但方向正好相反。心智模型相似性负向预测团队创造力,而心智模型正确性则正向预测团队创造力。两者还共同影响团队创造力,当成员心智模型正确性高且相似性低时,团队创造力最高;而当成员心智模型彼此相似但错误时,团队创造力最差。本研究首次将团队认知和团队创造力两个研究领域结合起来,研究结果有望丰富和拓展两个领域研究成果。

基于图变换的工作流建模及正确性分析

对工作流过程模型的研究是当前工作流研究的热点之一。现有工作流过程模型在可视化、描述全面性、过程分析以及形式化等方面难以均衡,健壮性和柔性不足。针对上述问题,基于图变换设计了一种新的工作流过程模型规范,并在这个工作流过程模型规范的基础上,利用TIGER工具实现了一个工作流建模与分析环境,使得相应工作流过程模型具有直观、简洁、形式化、描述能力强和便于分析的特点。

基于范畴论的业务目标模型形式化

面向目标需求语言(goal-oriented requirement language,GRL)模型聚焦于待定的需求,被广泛地应用于业务系统的初始需求建模,其模型的正确性影响到业务系统的开发质量。鉴于业务目标模型的形式化可以验证模型的正确性,提出了一种利用范畴论形式化GRL模型的方法。首先,依据GRL元模型结构,应用范畴论中的态射机制形式化描述GRL模型中目标与目标、目标与任务以及任务与任务等节点之间的关系;然后,通过增加范畴模型中的初始对象和终止对象,设计紧邻序列来表示多个目标与任务实施的因果关系;最后,设计业务目标模型系统的正确性结构性质。应用Web Payment系统实验表明,形式化业务范畴模型能够验证GRL模型的正确性,提高目标建模的质量。

无环配置问题研究

基于约束的配置问题提出一种无回溯搜索算法,通过弧相容技术将所有不相容的值删除,指导用户进行产品配置,并对其正确性进行了证明.探讨了将目前两种主流计算冲突解释方法应用到无环配置问题的可行性.

Finite element model updating for large span spatial steel structure considering uncertainties

In order to establish the baseline finite element model for structural health monitoring,a new method of model updating was proposed after analyzing the uncertainties of measured data and the error of finite element model.In the new method,the finite element model was replaced by the multi-output support vector regression machine(MSVR).The interval variables of the measured frequency were sampled by Latin hypercube sampling method.The samples of frequency were regarded as the inputs of the trained MSVR.The outputs of MSVR were the target values of design parameters.The steel structure of National Aquatic Center for Beijing Olympic Games was introduced as a case for finite element model updating.The results show that the proposed method can avoid solving the problem of complicated calculation.Both the estimated values and associated uncertainties of the structure parameters can be obtained by the method.The static and dynamic characteristics of the updated finite element model are in good agreement with the measured data.

Ranging Error Correction Based on a Prior Error Model

Wireless technology provides accurate positioning in indoor environments using time of arrival(TOA) based ranging techniques. However, the positioning accuracy is degraded due to the ranging errors caused by multipath and non-line-of-sight(NLOS) propagation. In this paper, a ranging error correction method is proposed to improve positioning performance. A TOA ranging error model(TREM) is built to provide the prior information for ranging error correction first. The mean value of TREM within a certain interval is used as the ranging error correction value(RECV). As the RECV may be unreasonable sometimes, we adjust it according to the actual positioning situation and then exploit the final RECV to correct ranging data. The experimental results show that the proposed method could well reduce ranging errors and the positioning performance is obviously improved when using corrected ranging data.

Fuzzy finite element model updating of bridges by considering the uncertainty of the measured modal parameters

It is significant to consider the effect of uncertainty of the measured modal parameters on the updated finite element(FE) model,especially for updating the FE model of practical bridges,since the uncertainty of the measured modal parameters cannot be ignored owing to the application of output-only identification method and the existence of the measured noise.A reasonable method is to define the objective of the FE model updating as the statistical property of the measured modal parameters obtained by conducting couples of identical modal tests,however,it is usually impossible to implement repeated modal test due to the limit of practical situation and economic reason.In this study,a method based on fuzzy finite element(FFM) was proposed in order to consider the effect of the uncertainty of the measured modal parameters on the updated FE model by using the results of a single modal test.The updating parameters of bridges were deemed as fuzzy variables,and then the fuzzification of objective of the FE model updating was proposed to consider the uncertainty of the measured modal parameters.Finally,the effectiveness of the proposed method was verified by updating the FE model of a practical bridge with the measured modal parameters.

The role of constant optimal forcing in correcting forecast models

In this paper,the role of constant optimal forcing(COF) in correcting forecast models was numerically studied using the well-known Lorenz 63 model.The results show that when we only consider model error caused by parameter error,which also changes with the development of state variables in a numerical model,the impact of such model error on forecast uncertainties can be offset by superimposing COF on the tendency equations in the numerical model.The COF can also offset the impact of model error caused by stochastic processes.In reality,the forecast results of numerical models are simultaneously influenced by parameter uncertainty and stochastic process as well as their interactions.Our results indicate that COF is also able to significantly offset the impact of such hybrid model error on forecast results.In summary,although the variation in the model error due to physical process is time-dependent,the superimposition of COF on the numerical model is an effective approach to reducing the influence of model error on forecast results.Therefore,the COF method may be an effective approach to correcting numerical models and thus improving the forecast capability of models.

NLO QCD corrections to Bc(B＊c) production around the Z pole at an e＋e- collider

The production of Bc and B＊ mesons at a Z-factory （an e＋e- collider operating at energies around the Z pole） is calculated up to the next-to-leading order （NLO） QCD accuracy. The results show that the dependence of the total cross sections on the renormalization scale/1 is suppressed by the corrections, and the NLO corrections enhance the total cross sections of B,. by 52% and of Bc＊ by 33% when the renormalization scale is taken at μ = 2mb. To observe the various behaviors of the production of the mesons Bc and Bc＊, such as the differential cross section vs. the out-going angle, the forward-backward asymmetry, and the distribution vs. the energy fraction z up to NLO QCD accuracy as well as the relevant K-factor （NLO to LO） for the production, are calculated, and it is pointed out that some of the observables obtained in the present work may be used as a specific precision test of the standard model.