WAVELET MODELING AND FORECASTING AND ITS APPLICATION IN THE CHINESE MONETARY MULTIPLIER

In this paper, a time_varying AR model is constructed by using the vector_space algorithm of compactly_supported biorthonormal wavelet transform. It is developed for forecasting narrow monetary multipliers in China .

Fully Coupled Fluid-Structure Interaction Model Based on Distributed Lagrange Multiplier/Fictitious Domain Method

This paper, with a finite element method, studies the interaction of a coupled incompressible fluid-rigid structure system with a free surface subjected to external wave excitations. With this fully coupled model, the rigid structure is taken as ＂fictitious＂ fluid with zero strain rate. Both fluid and structure are described by velocity and pressure. The whole domain, including fluid region and structure region, is modeled by the incompressible Navier-Stokes equations which are discretized with fixed Eulerian mesh. However, to keep the structure＇ s rigid body shape and behavior, a rigid body constraint is enforced on the ＂fictitious＂ fluid domain by use of the Distributed Lagrange Multipher/Fictitious Domain （DLM/ FD） method which is originally introduced to solve particulate flow problems by Glowinski et al. For the verification of the model presented herein, a 2D numerical wave tank is established to simulate small amplitude wave propagations, and then numerical results are compared with analytical solutions. Finally, a 2D example of fluid-structure interaction under wave dynamic forces provides convincing evidences for the method excellent solution quality and fidelity.

An anti-aliasing filtering of quantum images in spatial domain using a pyramid structure

As a part of quantum image processing,quantum image filtering is a crucial technology in the development of quantum computing.Low-pass filtering can effectively achieve anti-aliasing effects on images.Currently,most quantum image filterings are based on classical domains and grayscale images,and there are relatively fewer studies on anti-aliasing in the quantum domain.This paper proposes a scheme for anti-aliasing filtering based on quantum grayscale and color image scaling in the spatial domain.It achieves the effect of anti-aliasing filtering on quantum images during the scaling process.First,we use the novel enhanced quantum representation(NEQR)and the improved quantum representation of color images(INCQI)to represent classical images.Since aliasing phenomena are more pronounced when images are scaled down,this paper focuses only on the anti-aliasing effects in the case of reduction.Subsequently,we perform anti-aliasing filtering on the quantum representation of the original image and then use bilinear interpolation to scale down the image,achieving the anti-aliasing effect.The constructed pyramid model is then used to select an appropriate image for upscaling to the original image size.Finally,the complexity of the circuit is analyzed.Compared to the images experiencing aliasing effects solely due to scaling,applying anti-aliasing filtering to the images results in smoother and clearer outputs.Additionally,the anti-aliasing filtering allows for manual intervention to select the desired level of image smoothness.

基于随机-Nash-Harsanyi讨价还价博弈的光伏-氢储能多主体分散协同调度

将光伏(PV)主体与氢储能(HES)主体结合,形成PV-HES联合系统,是促进可再生能源就地消纳,实现能源低碳转型的有效措施。针对光伏出力随机干扰及主体互异等问题,提出PV-HES的分散协同调度模型。首先,基于Nash-Harsanyi讨价还价理论建立PV-HES的多主体合作运行模型,并将其等效转换为电能交易量确定子问题和电能交易成本确定子问题;然后,为了保护各主体隐私,运用改进的交替方向乘子法对上述两个子问题进行分布式求解;最后,在一个典型的PV-HES联合系统中进行算例仿真,以验证所提分散协同调度模型以及分布式求解算法的有效性。仿真结果表明,氢储能主体的运营成本分别降低了11.67%和10.48%,光伏运营商的收益提高了15.72%。此外,通过对交替方向乘子法的改进也提高了系统的求解效率。

基于先验驱动深度神经网络的泊松去噪变分模型

泊松去噪是一个典型的病态逆问题,其变分模型需要反复迭代和调节参数且计算效率低下,而纯深度学习模型往往依据经验设计网络且可解释性差。针对以上问题,在泊松噪声去噪变分模型的交替方向乘子法展开的基础上,设计端到端深度卷积神经网络,结合泊松噪声分布统计量与Bayesian最大后验概率估计推导出改进的泊松去噪变分模型。为了求解泊松去噪能量函数极值问题,采用交替方向乘子法,引入辅助变量、拉格朗日乘子和惩罚参数,将该问题分解为高斯去噪和图像重建两类交替优化子问题,先采用先验驱动的深度卷积神经网络实现高斯去噪,再通过解析迭代求解完成图像重建。实验结果表明,与基于非线性主成分分析、VST+BM3D、I+VST+BM3D和TRDPD的泊松去噪模型相比,改进模型在Set12数据集上的峰值信噪比均值分别提高2.73、0.87、0.57和0.50 dB,结构相似性均值分别提高0.148、0.046、0.020和0.047,在彩色图像及正电子发射断层扫描与计算机断层扫描图像上也明显提升了泊松去噪效果。上述实验结果证明了改进模型不仅有效去除了泊松噪声,而且避免了泊松去噪过程中产生的伪影和散斑等问题。

中国财政支出乘数有多大?——基于荟萃回归分析方法

财政支出乘数是评估财政政策绩效的重要标准,但已有研究关于中国财政支出乘数的测算结果并未达成一致。在当前我国政府财政治理目标任务日趋多元化和复杂化的背景下,如何有效地凝练与归纳已有研究对于加快提升财政治理能力具有承前启后的重要意义。本文采用荟萃回归分析方法对已有文献的实证分析结果进行系统性的定量分析,研究发现:第一,已有文献总体上支持我国财政支出政策具有显著乘数效应,但同时也存在财政支出乘数是否大于1的争议;第二,财政支出乘数估计值在不同研究特征下表现不同,发表于权威期刊、研究地方政府财政支出乘数和采用DSGE模型的文献倾向于测算得出更大的财政支出乘数;第三,我国财政支出的乘数效应具有显著的异质性,投资型支出的乘数效应大于消费型支出的乘数效应,长期乘数效应大于短期乘数效应;第四,微观计量模型近年来在财政政策绩效评估领域被广泛应用,相关文献测算得出的中国财政支出乘数相对较小,但平均来看仍然支持财政支出能够有效促进经济增长的观点。

An improved optimal elemental method for updating finite element models

The optimal matrix method and optimal elemental method used to update finite element models may not provide accurate results.This situation occurs when the test modal model is incomplete,as is often the case in practice.An improved optimal elemental method is presented that defines a new objective function,and as a byproduct,circumvents the need for mass normalized modal shapes,which are also not readily available in practice.To solve the group of nonlinear equations created by the improved optimal method,the Lagrange multiplier method and Matlab function fmincon are employed.To deal with actual complex structures, the float-encoding genetic algorithm(FGA)is introduced to enhance the capability of the improved method.Two examples,a 7- degree of freedom(DOF)mass-spring system and a 53-DOF planar frame,respectively,are updated using the improved method. The example results demonstrate the advantages of the improved method over existing optimal methods,and show that the genetic algorithm is an effective way to update the models used for actual complex structures.

Missile robust gain scheduling autopilot design using full block multipliers

Reduction of conservatism is one of the key and difficult problems in missile robust gain scheduling autopilot design based on multipliers.This article presents a scheme of adopting linear parameter-varying（LPV） control approach with full block multipliers to design a missile robust gain scheduling autopilot in order to eliminate conservatism.A model matching design structure with a high demand on matching precision is constructed based on the missile linear fractional transformation（LFT） model.By applying full block S-procedure and elimination lemma,a convex feasibility problem with an infinite number of constraints is formulated to satisfy robust quadratic performance specifications.Then a grid method is adopted to transform the infinite-dimensional convex feasibility problem into a solvable finite-dimensional convex feasibility problem,based on which a gain scheduling controller with linear fractional dependence on the flight Mach number and altitude is derived.Static and dynamic simulation results show the effectiveness and feasibility of the proposed scheme.

Methods of modeling relative growth rate

Background： Analysing and modelling plant growth is an important interdisciplinary field of plant science. The use of relative growth rates, involving the analysis of plant growth relative to plant size, has more or less independently emerged in different research groups and at different times and has provided powerful tools for assessing the growth performance and growth efficiency of plants and plant populations. In this paper, we explore how these isolated methods can be combined to form a consistent methodology for modelling relative growth rates. Methods： We review and combine existing methods of analysing and modelling relative growth rates and apply a combination of methods to Sitka spruce （Piceo sitchensis （Bong.） Carr.） stem-analysis data from North Wales （UK） and British Douglas fir （Pseudotsugd menziesii （Mirb.） Franco） yield table data. Results： The results indicate that, by combining the approaches of different plant-growth analysis laboratories and using them simultaneously, we can advance and standardise the concept of relative plant growth. Particularly the growth multiplier plays an important role in modelling relative growth rates. Another useful technique has been the recent introduction of size-standardised relative growth rates. Conclusions： Modelling relative growth rates mainly serves two purposes, 1） an improved analysis of growth performance and efficiency and 2） the prediction of future or past growth rates. This makes the concept of relative growth ideally suited to growth reconstruction as required in dendrochronology, climate change and forest decline research and for interdisciplinary research projects beyond the realm of plant science.

Optimization Mathematical Model of Pile Forces for Offshore Piled Breasting Dolphins

An optimization mathematical model of the pile forces for piled breasting dolphins in the open sea under various loading conditions is presented. The optimum layout with the well distributed pile forces and the least number of piles is achieved by the multiplier penalty function method. Several engineering cases have been calculated and compared with the result of the conventional design method. It is shown that the number of piles can be reduced at least by 10%～20% and the piles' bearing state is improved greatly.

A Coastal Zone Segmentation Variational Model and Its Accelerated ADMM Method

Effective and efficient SAR image segmentation has a significant role in coastal zone interpretation. In this paper, a coastal zone segmentation model is proposed based on Potts model. By introducing edge self-adaption parameter and modifying noisy data term, the proposed variational model provides a good solution for the coastal zone SAR image with common characteristics of inherent speckle noise and complicated geometrical details. However, the proposed model is difficult to solve due to to its nonlinear, non-convex and non-smooth characteristics. Followed by curve evolution theory and operator splitting method, the minimization problem is reformulated as a constrained minimization problem. A fast alternating minimization iterative scheme is designed to implement coastal zone segmentation. Finally, various two-stage and multiphase experimental results illustrate the advantage of the proposed segmentation model, and indicate the high computation efficiency of designed numerical approximation algorithm.

Multiply Charged Anions,Maximum Charge Acceptance,and Higher Electron Affinities of Molecules,Superatoms,and Clusters

The addition of electrons to form gas-phase multiply charged anions(MCAs)normally requires sophisticated experiments or calculations.In this work,the factors stabilizing the MCAs,the maximum electron uptake of gas-phase molecules,X,and the electronic stability of MCAs X^(Q-),are discussed.The drawbacks encountered when applying computational and/or conceptual density functional theory(DFT)to MCAs are highlighted.We develop and test a different model based on the valence-state concept.As in DFT,the electronic energy,E(N,v_(ex)),is a continuous function of the average electron number,N,and the external potential,v_(ex),of the nuclei.The valence-state-parabola is a second-order polynomial that allows extending E(N,v_(ex))to dianions and higher MCAs.The model expresses the maximum electron acceptance,Q_(max),and the higher electron affinities,A_Q,as simple functions of the firstelectron affinity,A_1,and the ionization energy,I,of the"ancestor"system.Thus,the maximum electron acceptance is Q_(max,calc)=1+12A_1/7(I-A_1).The ground-state parabola model of the conceptual DFT yields approximately half of this value,and it is termed Q_(max,GS)=?+A_1/(I-A_1).A large variety of molecules are evaluated including fullerenes,metal clusters,super-pnictogens,super-halogens(OF_3),super-alkali species(OLi_3),and neutral or charged transition-metal complexes,AB_(m )L_n^(0/+/-).The calculated second electron affinity A_(2,calc)=A_1-(7/12)(I-A_1)is linearly correlated to the literature references A_(2,lit) with a correlation coefficient R=0.998.A_2 or A_3 values are predicted for further 24 species.The appearance sizes,n_(ap)^(3-),of triply charged anionic clusters and fullerenes are calculated in agreement with the literature.

Testing for Cross-Sectional Dependence in a RandomEffects Model

This paper extends and generalizes the works of [1,2] to allow for cross-sectional dependence in the context of a two-way error components model and consequently develops LM test. The cross-sectional dependence follows the first order spatial autoregressive error (SAE) process and is imposed on the remainder disturbances. It is important to note that this paper does not consider alternative forms of spatial lag dependence other than SAE. It also does not allow for endogeneity of the regressors and requires the normality assumption to derive the LM test.

Distributed MPC for Reconfigurable Architecture Systems via Alternating Direction Method of Multipliers

This paper investigates the distributed model predictive control(MPC)problem of linear systems where the network topology is changeable by the way of inserting new subsystems,disconnecting existing subsystems,or merely modifying the couplings between different subsystems.To equip live systems with a quick response ability when modifying network topology,while keeping a satisfactory dynamic performance,a novel reconfiguration control scheme based on the alternating direction method of multipliers(ADMM)is presented.In this scheme,the local controllers directly influenced by the structure realignment are redesigned in the reconfiguration control.Meanwhile,by employing the powerful ADMM algorithm,the iterative formulas for solving the reconfigured optimization problem are obtained,which significantly accelerate the computation speed and ensure a timely output of the reconfigured optimal control response.Ultimately,the presented reconfiguration scheme is applied to the level control of a benchmark four-tank plant to illustrate its effectiveness and main characteristics.

分布式的温控负荷集群负荷跟随控制

温控负荷(thermostatically controlled loads,TCLs)集群作为一种灵活的可调度资源,已成为促进电网经济运行和帮助电网恢复稳定的有力手段之一。然而,由于温控负荷单体功率小、位置分散且参数各异,给调度带来了困难。为了灵活利用数量庞大的负荷侧资源进行负荷跟随控制,该文建立温控负荷的虚拟电池模型和负荷集群的聚合模型,并提出基于双层分布式通信网络的控制策略。上层利用分布式交替方向乘子法(alternating direction method of multipliers,ADMM)来解决不同负荷聚合器的最佳跟随功率问题,以确保跟随效益最优;下层提出基于快速分布式平均一致性算法的深度神经网络(deep neural networks,DNN)的方法,使得聚合器内部的所有温控负荷以相等的虚拟电池荷电状态(state of charge,SoC)快速共享上层得到的跟随功率,并有效减少了通信数据量。不同时间尺度的算例验证提出的控制策略能够实现快速的负荷跟随,并保证用户侧的效益。

面向耦合系统的交替方向滚动时域电压分层协同优化控制

我国北方地区普遍存在由风、光等新能源场站与传统同步机组构成并经外送通道功率送出的耦合系统,其新能源单元并网点、场站并网点及耦合系统功率外送并网点均需满足各自的电压安全标准,给电压安全控制带来了严峻挑战。面向耦合系统电压调控问题,该文结合耦合系统单元-场站-系统的物理层级特征,确定了系统层-场站层的电压分层协同控制结构,在各层级内兼顾运行网损优化和电压控制要求,协调各类无功控制资源,建立综合模型预测控制(MPC)和交替方向乘子法(ADMM)的网损优化与电压校正双模式自适应切换的滚动时域控制策略,实现耦合系统的分布式协同电压控制。在修改后的IEEE-14节点耦合系统和大连某区域耦合系统进行仿真,结果表明了该控制策略的有效性和适用性。

基于模型预测控制的多微网系统2阶段优化调度

针对多微网系统集中式优化所带来的巨大计算压力以及源荷不确定性给系统稳定运行所造成的影响,提出了基于模型预测控制的多微网系统2阶段优化调度方法。针对日前阶段,考虑微网间源荷时空互补特性,以微网间热电交互功率、各微网中可控微源出力以及储能系统出力为优化变量,建立最小化多微网运行成本的日前优化模型,并利用同步型交叉方向乘子算法求解日前调度计划;针对日内阶段,为应对源荷预测偏差,用模型预测控制对储能系统进行合理调控,以平滑热、电网联络线,跟踪日前调度计划。算例结果表明,所提优化调度方法可缓解集中式优化的计算压力,提升系统运行的经济性与可靠性。

基于维纳滤波的体育运动视频模糊图像复原方法

为解决由噪声、拍摄目标与摄像机间相对运动导致的视频成像质量下降的问题,提出一种基于维纳滤波的体育运动视频模糊图像复原方法。图像复原过程即为图像退化的逆过程,在复原前通过噪声及模糊图像构建退化模型。使用拉格朗日乘数法构建退化模型复原约束条件,计算维纳滤波函数中运动图像的模糊角度和模糊尺度,完成图像复原全过程。实验表明在不同的相对运动速度下,所提方法能够有效地去除模糊图像梯度效应,使图像中没有较明显的模糊点,能够基本满足体育运动对视频图像清晰度的要求。

电动汽车与直流配电网协同的分布式自适应滚动预测调度

为充分挖掘电动汽车(EV)的灵活调度潜力,提出了EV与直流配电网协同的分布式自适应滚动预测调度方法。首先,建立了电压源型换流器、储能及直流配电网潮流的数学模型;然后,构建了不可调度、只充电和可充放电3类EV充电偏好的数学模型,并以日电能损耗和弃光电量的加权和最小为目标建立了直流配电网自适应滚动预测调度模型,通过实时EV集群的取车时间动态更新调度窗口,以满足每辆EV的期望电量需求;最后,建立了直流配电网分布式滚动预测调度模型,并采用交替方向乘子法实现分布式求解,以解决集中式调度通信量大的问题。仿真结果表明,通过对EV与直流配电网灵活性资源的协同调度可显著降低电能损耗、提升分布式电源接纳能力,同时,所采用的分布式算法具有良好的收敛性能和计算速度。

含多球铰间隙并联机构动力学建模与响应分析

为了分析多个球铰间隙对并联机构动力学响应的影响,本文以3-SPS-S空间并联机构为研究对象,在Flores法向接触力模型和改进的Coulomb摩擦力模型的基础上,推导出球铰间隙处的碰撞力模型。采用Lagrange乘子法建立了含多个球铰间隙的并联机构动力学模型。利用Matlab软件,通过四阶Runge-Kutta解法求解此模型,分析球铰间隙如何影响机构的动力学响应,并应用ADAMS软件虚拟样机仿真。研究表明:球面副间隙对动平台角加速度和间隙处的碰撞力影响较大,且间隙数量越多,机构稳定性越差。本文为考虑多个球铰间隙并联机构刚体动力学模型的建立和响应分析提供理论依据,对准确的预测和控制含球铰间隙机构的动力学特性具有重要意义。