一种离散非线性随机系统模型的非线性结构的自校正控制器

本文给出了一种描述离散非线性随机系统的数学模型,它是CARMA模型的一种扩展,双线性系统模型是它的一种特殊形式,并给出了新模型下自校正控制器的算法,它将CARMA模型下的算法结构从线性扩展到非线性。

基于随机模型的软实实时时系统的任务期望可调调度度性

本文基于随机模型研究了软实时系统中任务的可调度性特征,提出了期望可调度性的概念.期望可调度性是与实时任务到达时间t相关的,因此,提出的方法能研究任务子集在任意给定时间间隔的可调度性特征.本文给出了期望可调度性的条件,如果任务的持续时间满足该条件,则实时任务具有期望可调度性.基于理论结果的数值分析与模拟结果是一致的,这表明当软实时系统的负载率小于69%(某些确定性模型提供的)时,实时任务总是期望可调度的.这一结果也表明基于随机模型的期望可调度性方法能为软实时系统的任务可调度性分析提供一个更大的阈值和更好的适应性.

随机开放量子系统模型及其反馈控制的特性分析

研究了不同情况下基于连续测量的随机开放量子系统模型。对于受到测量影响的不同开放量子系统模型,分析了模型建立的条件、模型的组成及其影响;对于所简化的模型,分析了其简化的过程;同时对不同模型之间的关系进行对比分析。基于估计状态的随机开放量子系统的反馈控制,分别对目前已有的开关控制和连续性控制在本征态之间状态转移的控制思想、所具有的特性、控制效果、适用条件、改进过程等进行了对比研究。同时还探讨了环境退相干和时间延迟影响下反馈控制器的设计。

基于通用即插即用协议服务发现的随机服务系统模型

在智能家居网络设备自动发现过程中,网络设备端随机独立地选择延时发送服务响应消息,通常出现严重的消息拥塞现象。为解决智能家居网络中服务响应消息拥塞问题,以智能家居标准协议——通用即插即用(UPn P)进行自动发现设备为例,考虑不同应用场景中对服务发现过程的可靠性和实时性有不同要求,提出一种基于UPn P服务发现的随机服务系统模型。设计了集成系统响应指标和等待指标的通信损益函数,推导得到了最佳缓存队列长度与损益系数之间的关系。通过对比不同缓存队列长度中响应消息的到达时间、离开时间、等待时间和停留时间,验证了设计损益指标的必要性和随机服务系统模型的可行性。

大水矿山开采水环境系统失效致灾机理

基于大水矿山开采水环境由人工排水系统及天然的地下水系统共同构成,通过系统分析方法,构建大水矿山排水-地下水开采水环境系统。在此基础上,进行大水矿山开采水环境系统失效致灾机理研究,建立大水矿山排水-地下水开采环境系统随机模型及系统失效致灾判据。将所建立的模型及判据应用于凡口铅锌矿大水地下开采矿山。研究结果表明:在一定时域范围内,模型可有效识别系统的灾害状态;系统失效致灾是系统输入流量大于输出流量,系统水位离散程度随时间不断增大,以及系统自身结构承受安全水位的能力过低共同作用的结果,从影响程度来讲,系统流量差的变化对灾害影响最大,其次为安全水位,最后为系统的随机作用;所建立的系统模型及系统失效致灾判据具有实用性和有效性,研究成果可为大水矿山开采水害防治提供有效的技术支持。

Rank-Defect Adjustment Model for Survey-Line Systematic Errors in Marine Survey Net

In this paper,the structure of systematic and random errors in marine survey net are discussed in detail and the adjustment method for observations of marine survey net is studied,in which the rank_defect characteristic is discovered first up to now.On the basis of the survey_line systematic error model,the formulae of the rank_defect adjustment model are deduced according to modern adjustment theory.An example of calculations with really observed data is carried out to demonstrate the efficiency of this adjustment model.Moreover,it is proved that the semi_systematic error correction method used at present in marine gravimetry in China is a special case of the adjustment model presented in this paper.

洛阳市中小学校车需求量预测

本文通过调查洛阳市中小学生上下学各种交通方式所占比率，计算出洛阳市市区校车市场的潜在客流量。根据近几年的潜在客流量，首先采用加权平滑预测模型、灰色系统模型和灰色——马尔柯夫预测模型进行初步预测，然后采用组合预测模型来对未来客流量进行最终预测。根据最终预测结果，计算出洛阳市市区普及校车工程所需要的校车数量。

INTRUSION DETECTION BASED ON THE SECOND-ORDER STOCHASTIC MODEL

This paper presents a new method based on a second-order stochastic model for computer intrusion detection.The results show that the performance of the second-order stochastic model is better than that of a first-order stochastic model.In this study,different window sizes are also used to test the performance of the model.The detection results show that the second-order stochastic model is not so sensitive to the window size,comparing with the first-order stochastic model and other previous researches.The detection result of window sizes 6 and 10 is the same.

Longitudinal-Random-Field Mixed Ising Model with Arbitrary Spins

The longitudinal-random-fieM mixed Ising model consisting of arbitrary spin values has been studied by the use of an effective field theory with correlations （EFT）. The phase diagrams of systems with mixed spins： σ = 1/2, S = 1; σ = 1/2, S = 3/2 are plotted. Not only the discontinuity at T = 0 K, is found when both longitudinal fields are trimodal distributed, but also the trieritical behavior is observed in these phase diagrams between the bimodal and trimodal distributions of longitudinal fields, which is different from the single-spin one. The appearance of tricritical point is independent of the coordination number and spin values.

Two-stage stochastic approach for spinning reserve allocation in dynamic economic dispatch

A novel approach was proposed to allocate spinning reserve for dynamic economic dispatch.The proposed approach set up a two-stage stochastic programming model to allocate reserve.The model was solved using a decomposed algorithm based on Benders' decomposition.The model and the algorithm were applied to a simple 3-node system and an actual 445-node system for verification,respectively.Test results show that the model can save 84.5 US $ cost for the testing three-node system,and the algorithm can solve the model for 445-node system within 5 min.The test results also illustrate that the proposed approach is efficient and suitable for large system calculation.

Stochastic Modeling of Total Ground Irradiance of Horizontal Surface

This paper describes relatively simple stochastic model of the total ground irradiance of horizontal surface. For this purpose clearness index is modeled as a stochastic signal. The parameters of clearness index stochastic signal are chosen to fit values of daily mean insolation for each month for the location of Zagreb, Croatia. Complete model has been done in MATLAB. This model can be used for Monte Carlo simulations of technical solar systems such as photovoltaic systems or solar thermal energy systems.

RobustL_1 model reduction for stochastic time-delay systems

This paper investigates the problem of robust L1 model reduction for continuous-time uncertain stochastic time-delay systems. For a given mean-square stable system, our purpose is to construct reduced-order systems, such that the error system between these two models is mean-square asymptotically stable and has a guaranteed L1 (also called peak-to-peak) performance. The peak-to-peak gain criterion is first established for stochastic time-delay systems, and the corresponding model reduction problem is solved by using projection lemma. Sufficient conditions are obtained for the existence of admissible reduced-order models in terms of linear matrix inequalities (LMIs) plus matrix inverse constraints. Since these obtained conditions are not expressed as strict LMIs, the cone complementarity linearization (CCL) method is exploited to cast them into nonlinear minimization problems subject to LMI constraints, which can be readily solved by standard numerical software. In addition, the development of reduced-order models with special structures, such as the delay-free model, is also presented. The efficiency of the proposed methods is demonstrated via a numerical example.

A Stochastic Model on One-Unit Repairable Systems with Multiple Degenerative States

This paper studies a maintenance model for an one-unit degenerative system with multiple failure states based on the proportional hazards and proportional reversed hazards models. The authors investigate how the variation of system configuration parameters have an impact on both operating and repair times and hence the system performance. Furthermore, the authors also derive the explicit expression for the long-run average cost per unit time. An algorithm to locate the optimal number of repairs in a renewal cycle is discussed as well.

Articulated Estimator Random Field and Geometrical Approach Applied in System Identification

A new point of view of robust statistics based on a geometrical approach is tackled in this paper. Estimation procedures are carried out from a new robust cost function based on a chaining of elementary convex norms. This chain is randomly articulated in order to treat more efficiently natural outliers in data-set. Estimated parameters are considered as random fields and each of them, named articulated estimator random field （AERF） is a manifold or stratum of a stratified space with Riemannian geometry properties, From a high level excursion set, a probability distribution model Mata is presented and a system model validation geometric criterion （SYMOVAGEC） for system model structures Msys based on Rieeian scalar curvatures is proposed. Numerical results are drawn in a context of system identification.

Mean field limit of a dynamical model of polymer systems

This paper provides a mathematically rigorous foundation for self-consistent mean field theory of the polymeric physics. We study a new model for dynamics of mono-polymer systems. Every polymer is regarded as a string of points which are moving randomly as Brownian motions and under elastic forces. Every two points on the same string or on two different strings also interact under a pairwise potential V. The dynamics of the system is described by a system of N coupled stochastic partial differential equations （SPDEs）. We show that the mean field limit as N -＋ c~ of the system is a self-consistent McKean-Vlasov type equation, under suitable assumptions on the initial and boundary conditions and regularity of V. We also prove that both the SPDE system of the polymers and the mean field limit equation are well-posed.

Subspace-based identification of discrete time-delay system

We investigate the identification problems of a class of linear stochastic time-delay systems with unknown delayed states in this study. A time-delay system is expressed as a delay differential equation with a single delay in the state vector. We first derive an equivalent linear time-invariant(LTI) system for the time-delay system using a state augmentation technique. Then a conventional subspace identification method is used to estimate augmented system matrices and Kalman state sequences up to a similarity transformation. To obtain a state-space model for the time-delay system, an alternate convex search(ACS) algorithm is presented to find a similarity transformation that takes the identified augmented system back to a form so that the time-delay system can be recovered. Finally, we reconstruct the Kalman state sequences based on the similarity transformation. The time-delay system matrices under the same state-space basis can be recovered from the Kalman state sequences and input-output data by solving two least squares problems. Numerical examples are to show the effectiveness of the proposed method.