一种过程方程组分解方法及其在催化裂化反应——再生模型中的 …

Ｒａｍｉｒｅｚ算法是一种对过程方程组进行分解的算法，此算法将过程方程组分解后，可以使求解计算更快速可靠，本文指出，选择输出变量顺序不同，过程方程组分解过程中形成的平台变量也不同，从而影响决策变量的选择，在确定决策变量时，应优先取平台变量为决策变量，将Ｒａｍｉｒｅｚ算法用于催化裂化反应－再生模型的分解，找出合适的求解策略，验证了提出了观点。     

一种过程方程组分解方法及其在催化裂化反应——再生模型中的应用

Ｒａｍｉｒｅｚ算法是一种对过程方程组进行分解的算法。此算法将过程方程组分解后，可以使求解计算更快速可靠。本文指出，选择输出变量顺序不同，过程方程组分解过程中所形成的平台变量也不同，从而影响决策变量的选择。在确定决策变量时，应优先选取平台变量为决策变量。将Ｒａｍｉｒｅｚ算法用于催化裂化反应再生模型的分解，找出了合适的求解策略，验证了提出的观点。     

基于子结构的航天相机冲击动力学仿真

在航天相机结构的谱响应分析过程中，由于系统过于复杂而导致方程规模庞大，以至于计算机求解难以实现。为缩减系统自由度，该文采用子结构技术划分相机有限元模型，然后逐个分析每个子结构，并在此基础上经模态综合计算了航天相机结构的冲击动力学响应。计算结果表明，该方法可以很好地利用其内部自由度凝聚的特点，使得大规模计算容易实现。     

基于模块环境的过程系统综合策略的研究

模块环境下过程模拟系统的研究已较成熟,并开发出许多模拟软件。过程系统综合的研究多采用基于方程的方法,这使得过程模拟研究成果无法得到很好的利用。为了以模块环境的化工过程模拟系统为基础,开发过程综合系统,作者提出了新的三层次化工过程系统综合的解算策略,以结构层中引入P矩阵并在解算过程中引入虚拟断裂物流与虚拟变量。 通过实例计算表明本文所用的方法可以使计算过程更加灵活,提高了计算速度和效率,改善了流程综合的收敛性能。     

使用体渲染进行的快速全局照明

提出了一种基于体渲染的快速全局照明方法，用于实时计算复杂的直接照明和间接照明。该方法使用一系列预先计算的图像数据来表示照明在特定空间中的分布，在实时渲染时通过对这些空间数据的重组来得到给定位置处的光强。计算过程分为预处理和实时渲染两部分：首先，针对每一个物体计算出该物体对周围空间辐照度的影响，并存储在体数据结构中；然后，在实时渲染过程中，利用已有的体数据重建出给定点的辐照度，实现照明。该方法可以计算任意形式的光源照明以及间接漫射。     

基于子系统间物流联接的大系统柔性分析

研究了对带有子系统间物流联接的大系统的柔性分析方法，采用化工过程系统中的柔性指数来衡量大系统的柔性大小。在化工过程系统柔性指数的计算方法的基础上，本文首先提出增加三组附加约束来提高计算大系统的柔性指数的速度；然后，本文又提出了逐步计算出每个子系统的柔性指数的方法，从而可以更全面地了解大系统的柔性状况；最后。用一个海水利用产业链作为案例研究表明了上述方法的有效性。本文的方法在该类大系统，例如生态工业系统的建设中具有重要的作用。     

基于存储过程的科研绩效统计分析系统的实现

根据存储过程的可移植性、可重用性、安全性和可伸缩性等优势,利用存储过程分析设计一种科研绩效统计分析的计算方法,即将科研绩效统计分析所涉及的计算方法用存储过程来实现;且使整个统计分析计算集中在一起,这样既可以降低用Java类的程序冗余性,也可以提高数据处理速度、用户操作的方便性;这些统计分析功能主要包括绩效成果分配比例分配与报表输出.最后测试表明,随着统计分析的数目增多,采用存储过程的方法比传统方法有明显的优点.     

过程环境PoCASE的设计

ＰｏＣＡＳＥ过程环境是一个原型系统，用以支持软件过程的方法学开发，实例化和实施。本文探讨了这个过程工作模型，并用模型的各部件来描述它的体系结构，该体系结构主要软件过程的产品以及高级过程所支持的生产周期。本文的核心是讨论建立和裁剪过程模型的几步步骤，并给出支持这种描述的方法，其中过程模型是用混合过程语言建立的。本文的工作可以看作是过程环境的基础。     

开放普适计算环境的实现

开放系统已经成为当今计算机界广泛倡导并积极遵循的策略。从开放系统的基本特征出发，导出描述开放系统的轮廓框架(AUSPICE)，通过对轮廓中各个组成部分，选用一定的标准就可以实现一个开放系统。但实现一个完全的开放系统是一个长期的过程，而且对于具体应用环境和需求．其实现过程各有不同。本文针对普适计算环境，首先分析了开放性对于普适计算环境的重要性和必然性，同时针对普适计算环境的特点，对开放系统的轮廓框架扩充为AUSPICAE，最后提出了适合普适计算环境的开放系统实现过程模型。     

基于半马尔可夫过程容错导航系统可靠性分析的化简

在容错导航系统中,当采用序贯的方法进行故障检测或者对系统的某些参数采用滤波以后,可以利用半马尔可夫过程理论分析系统的可靠性。本文应用具有时间尺度的半马尔可夫极限定理,对容错导航系统半马尔可夫可靠性分析过程进行了化简,减少了计算量,简化了计算过程。     

A new linguistic out-sample approach of fuzzy time series for daily forecasting of Malaysian electricity load demand

The fuzzy logical relationships and the midpoints of interval have been used to determine the numerical in-out-samples forecast in the fuzzy time series modeling. However, the absolute percentage error is still yet significantly improved. This can be done where the linguistics time series values should be forecasted in the beginning before the numerical forecasted values obtained. This paper introduces the new approach in determining the linguistic out-sample forecast by using the index numbers of linguistics approach. Moreover, the weights of fuzzy logical relationships are also suggested to compensate the presence of bias in the forecasting. The daily load data from National Electricity Board (TNB) of Malaysia is used as an empirical study and the reliability of the proposed approach is compared with the approach proposed by Yu. The result indicates that the mean absolute percentage error (MAPE) of the proposed approach is smaller than that as proposed by Yu. By using this approach the linguistics time series forecasting and the numerical time series forecasting can be resolved.     

连续时间混沌系统控制与同步的状态反馈方法

将连续时间混沌系统的控制与同步问题统一处理,在系统的非线性是Lipschitz非线性的条件下,基于Lyapunov稳定性理论,提出一种实现连续时间混沌系统控制与同步的状态反馈方法。无论驱动系统处于何种状态,该方法都可使响应系统按照驱动系统给定的轨道演化。该方法对系统参数不匹配及噪声干扰具有一定的鲁棒性。数值仿真结果表明了所提出方法的有效性。     

GBS业务流量的隐马尔可夫模型

简单介绍了GBS(全球广播业务)系统, 对其承载的业务进行分析, 提出了基于隐马尔可夫模型的业务流量建模方法. 在Qualnet中搭建了GBS仿真场景, 生成并测量了业务流量. 并在Matlab中实现了对GBS系统中四种业务流量的建模. 结果表明, 该模型只选用数据包大小和数据包间隔等受加密技术影响不大的流量特征进行建模, 更能真实地反映GBS系统的业务流量特征. 采用离散型的随机变量, 降低了建模的计算复杂度, 减少了建模时间, 提高了实时性.     

Fuzzy weighted support vector regression with a fuzzy partition.

The problem of the traditional support vector regression (SVR) approach, referred to as the global SVR approach, is the incapability of interpreting local behavior of the estimated models. An approach called the local SVR approach was proposed in the literature to cope with this problem. Although the local SVR approach can indeed model local behavior of models better than the global SVR approach does, the local SVR approach still has the problem of boundary effects, which may generate a large bias at the boundary and also need more time to calculate. In this paper, the fuzzy weighted SVR with a fuzzy partition is proposed. Because the concept of locally weighted regression is not used in the proposed approach, the boundary effects will not appear. The proposed method first employs the fuzzy c-mean clustering algorithm to split training data into several training subsets. Then, the local-regression models (LRMs) are independently obtained by the SVR approach for each training subset. Finally, those LRMs are combined by a fuzzy weighted mechanism to form the output. Experimental results show that the proposed approach needs less computational time than the local SVR approach and can have more accurate results than the local/global SVR approaches does.     

云计算环境下聚合服务的随机模型检测

当前缺乏对聚合云服务正确性、响应时间和费用约束统一进行验证的有效方法。扩展基本工作流模式,增强概率、随机、不确定选择的刻画能力,用于定义聚合云服务的服务流程,将流程定义转换为连续时间Markov回报过程,扩展连续随机回报逻辑CSRL,用以刻画增强行为描述的统一验证属性,给出随机模型检测方法。分析表明,该方法能有效刻画运行时云服务动态行为并对其正确性、可靠性进行验证。     

ASTRA - A Novel interest measure for unearthing latent temporal associations and trends through extending basic gaussian membership function

Time profiled association mining is one of the important and challenging research problems that is relatively less addressed. Time profiled association mining has two main challenges that must be addressed. These include addressing i) dissimilarity measure that also holds monotonicity property and can efficiently prune itemset associations ii) approaches for estimating prevalence values of itemset associations over time. The pioneering research that addressed time profiled association mining is by J.S. Yoo using Euclidean distance. It is widely known fact that this distance measure suffers from high dimensionality. Given a time stamped transaction database, time profiled association mining refers to the discovery of underlying and hidden time profiled itemset associations whose true prevalence variations are similar as the user query sequence under subset constraints that include i) allowable dissimilarity value ii) a reference query time sequence iii) dissimilarity function that can find degree of similarity between a temporal itemset and reference. In this paper, we propose a novel dissimilarity measure whose design is a function of product based gaussian membership function through extending the similarity function proposed in our earlier research (G-Spamine). Our approach, MASTER (Mining of Similar Temporal Associations) which is primarily inspired from SPAMINE uses the dissimilarity measure proposed in this paper and support bound estimation approach proposed in our earlier research. Expression for computation of distance bounds of temporal patterns are designed considering the proposed measure and support estimation approach. Experiments are performed by considering naïve, sequential, Spamine and G-Spamine approaches under various test case considerations that study the scalability and computational performance of the proposed approach. Experimental results prove the scalability and efficiency of the proposed approach. The correctness and completeness of proposed approach is also proved analytically.

     

Estimation of CFO and STO for an OFDM using general ICI self-cancellation precoding

This study presents an efficient carrier-frequency-offset (CFO) and symbol-timing-offset (STO) estimation algorithm for time-dispersive orthogonal frequency division multiplexing (OFDM) system using a general inter-carrier interference (ICI) self-cancellation scheme. This study takes advantage of the time shift invariant property in the precoded signal to estimate the CFO. The proposed algorithm first stacks the receive time samples spaced by a pre-determined time interval into sample vectors, which can be expressed in a form having a CFO-directed response vector. This CFO-directed structure enables the proposed approach to estimate the CFO by using the multiple signal classification (MUSIC) algorithm in the time domain. Equalization is required before the MUSIC algorithm to remove the scaling factor generated in the signal stacking. Using the CFO estimate, the proposed approach compensates for the frequency error in the receive signal and then estimates the STO by invoking the MUSIC algorithm in the frequency domain. Unlike conventional algorithms, in addition to having a larger CFO estimation range linearly proportional to the precoding order, the proposed approach can easily handle the case of fractional STO. This study presents some statistical analysis of the undesired equalization residues and the mean square error of the perturbed MUSIC algorithm to provide further insights into the proposed approach.     

基于主题特征的关键词抽取

为了使抽取出的关键词更能反映文档主题,提出了一种新的词的主题特征(topic feature,TF)计算方法,该方法利用主题模型中词和主题的分布情况计算词的主题特征。并将该特征与关键词抽取中的常用特征结合,用装袋决策树方法构造一个关键词抽取模型。实验结果表明提出的主题特征可以提升关键词抽取的效果,同时验证了装袋决策树在关键词抽取中的适用性。     

Low-complexity time synchronization for energy-constrained wireless sensor networks: Dual-Clock delayed-message approach

Due to the ability of sensor nodes to collaborate, time synchronization is essential for many sensor network operations. With the aid of hardware capabilities, this work presents a novel time synchronization method, which employs a dual-clock delayed-message approach, for energy-constrained wireless sensor networks (WSNs). To conserve WSN energy, this study adopts the flooding time synchronization scheme based on one-way timing messages. Via the proposed approach, the maximum-likelihood (ML) estimation of time parameters, such as clock skew and clock offset, can be obtained for time synchronization. Additionally, with the proposed scheme, the clock skew and offset estimation problem will be transformed into a problem independent of random delay and propagation delay. The ML estimation of link propagation delay, which can be used for localization systems in the proposed scenario, is also obtained. In addition to good performance, the proposed method has low complexity.     

A two-step approach for model reduction in flexible multibody dynamics

In this work, a two-step approach for model reduction in flexible multibody dynamics is proposed. This technique is a combination of the Krylov-subspace method and a Gramian matrix based reduction approach that is particularly suited if a small reduced-order model of a system charged with many force-inputs has to be generated. The proposed methodology can be implemented efficiently using sparse matrix techniques and is therefore applicable to large-scale systems too. By a numerical example, it is demonstrated that the suggested two-step approach has very good approximation capabilities in the time as well as in the frequency domain and can help to reduce the computation time of a numerical simulation significantly.