A SUPERLINEARLY CONVERGENT SPLITTING FEASIBLE SEQUENTIAL QUADRATIC OPTIMIZATION METHOD FOR TWO-BLOCK LARGE-SCALE SMOOTH OPTIMIZATION

This paper discusses the two-block large-scale nonconvex optimization problem with general linear constraints.Based on the ideas of splitting and sequential quadratic optimization(SQO),a new feasible descent method for the discussed problem is proposed.First,we consider the problem of quadratic optimal(QO)approximation associated with the current feasible iteration point,and we split the QO into two small-scale QOs which can be solved in parallel.Second,a feasible descent direction for the problem is obtained and a new SQO-type method is proposed,namely,splitting feasible SQO(SF-SQO)method.Moreover,under suitable conditions,we analyse the global convergence,strong convergence and rate of superlinear convergence of the SF-SQO method.Finally,preliminary numerical experiments regarding the economic dispatch of a power system are carried out,and these show that the SF-SQO method is promising.

High-Order Decoupled and Bound Preserving Local Discontinuous Galerkin Methods for a Class of Chemotaxis Models

In this paper,we explore bound preserving and high-order accurate local discontinuous Galerkin(LDG)schemes to solve a class of chemotaxis models,including the classical Keller-Segel(KS)model and two other density-dependent problems.We use the convex splitting method,the variant energy quadratization method,and the scalar auxiliary variable method coupled with the LDG method to construct first-order temporal accurate schemes based on the gradient flow structure of the models.These semi-implicit schemes are decoupled,energy stable,and can be extended to high accuracy schemes using the semi-implicit spectral deferred correction method.Many bound preserving DG discretizations are only worked on explicit time integration methods and are difficult to get high-order accuracy.To overcome these difficulties,we use the Lagrange multipliers to enforce the implicit or semi-implicit LDG schemes to satisfy the bound constraints at each time step.This bound preserving limiter results in the Karush-Kuhn-Tucker condition,which can be solved by an efficient active set semi-smooth Newton method.Various numerical experiments illustrate the high-order accuracy and the effect of bound preserving.

A COMBINED PARAMETRIC QUADRATIC PROGRAMMING AND PRECISE INTEGRATION METHOD BASED DYNAMIC ANALYSIS OF ELASTIC-PLASTIC HARDENING/SOFTENING PROBLEMS

The objective of the paper is to develop a new algorithm for numerical solution of dynamic elastic-plastic strain hardening/softening problems. The gradient dependent model is adopted in the numerical model to overcome the result mesh-sensitivity problem in the dynamic strain softening or strain localization analysis. The equations for the dynamic elastic-plastic problems are derived in terms of the parametric variational principle, which is valid for associated, non-associated and strain softening plastic constitutive models in the finite element analysis. The precise integration method, which has been widely used for discretization in time domain of the linear problems, is introduced for the solution of dynamic nonlinear equations. The new algorithm proposed is based on the combination of the parametric quadratic programming method and the precise integration method and has all the advantages in both of the algorithms. Results of numerical examples demonstrate not only the validity, but also the advantages of the algorithm proposed for the numerical solution of nonlinear dynamic problems.

MIXED ENERGY METHOD FOR SOLUTION OF QUADRATIC PROGRAMMING PROBLEMS AND ELASTIC-PLASTIC ANALYSIS OF TRUSS STRUCTURES

A new algorithm for the solution of quadratic programming problemsis put forward in terms of the mixed energy theory and is furtherused for the incremental solution of elastic-plastic trussstructures. The method proposed is different from the traditionalone, for which the unknown variables are selected just in one classsuch as displacements or stresses. The present method selects thevariables in the mixed form with both displacement and stress. As themethod is established in the hybrid space, the information found inthe previous incremental step can be used for the solution of thepresent step, making the algorithm highly effi- cient in thenumerical solution process of quadratic programming problems. Theresults obtained in the exm- ples of the elastic-plastic solution ofthe truss structures verify what has been predicted in thetheoretical anal- ysis.

Computing the Enclosures Eigenvalues Using the Quadratic Method

In this article, we compute the enclosures eigenvalues (upper and lower bounds) using the quadratic method. The Schrodinger operator (A) (harmonic and anharmonic oscillator model) has used as an example. We study a new technique to get more accurate bounds. We compare our results with Boulton and Strauss method.

A GLOBAL LINEAR AND LOCAL QUADRATIC SINGLE-STEP NONINTERIOR CONTINUATION METHOD FOR MONOTONE SEMIDEFINITE COMPLEMENTARITY PROBLEMS

A noninterior continuation method is proposed for semidefinite complementarity problem （SDCP）. This method improves the noninterior continuation methods recently developed for SDCP by Chen and Tseng. The main properties of our method are： （i） it is well d.efined for the monotones SDCP; （ii） it has to solve just one linear system of equations at each step; （iii） it is shown to be both globally linearly convergent and locally quadratically convergent under suitable assumptions.

AN INEXACT LAGRANGE-NEWTON METHOD FOR STOCHASTIC QUADRATIC PROGRAMS WITH RECOURSE

In this paper,two-stage stochastic quadratic programming problems with equality constraints are considered.By Monte Carlo simulation-based approximations of the objective function and its first(second)derivative,an inexact Lagrange-Newton type method is proposed.It is showed that this method is globally convergent with probability one.In particular,the convergence is local superlinear under an integral approximation error bound condition.Moreover,this method can be easily extended to solve stochastic quadratic programming problems with inequality constraints.

The Appearance of Noise Terms in Modified Adomian Decomposition Method for Quadratic Integral Equations

In this paper, we apply the modified Adomian Decomposition Method to get the numerical solutions of Quadratic integral equations. The appearance of noise terms in Decomposition Method was investigated. The method was described along with several examples.

A New Numerical Method for Solving the Stokes Problem Using Quadratic Programming

In this paper we present a new method for solving the Stokes problem which is a constrained optimization method. The new method is simpler and requires less computation than the existing methods. In this method we transform the Stokes problem into a quadratic programming problem and by solving it, the velocity and the pressure are obtained.

GLOBAL LINEAR AND QUADRATIC ONE-STEP SMOOTHING NEWTON METHOD FOR VERTICAL LINEAR COMPLEMENTARITY PROBLEMS

A one_step smoothing Newton method is proposed for solving the vertical linear complementarity problem based on the so_called aggregation function. The proposed algorithm has the following good features: (ⅰ) It solves only one linear system of equations and does only one line search at each iteration; (ⅱ) It is well_defined for the vertical linear complementarity problem with vertical block P 0 matrix and any accumulation point of iteration sequence is its solution.Moreover, the iteration sequence is bounded for the vertical linear complementarity problem with vertical block P 0+R 0 matrix; (ⅲ) It has both global linear and local quadratic convergence without strict complementarity. Many existing smoothing Newton methods do not have the property (ⅲ).

Minimizing Complementary Pivots in a Simplex-Based Solution Method for a Quadratic Programming Problem

The paper presents an approach for avoiding and minimizing the complementary pivots in a simplex based solution method for a quadratic programming problem. The linearization of the problem is slightly changed so that the simplex or interior point methods can solve with full speed. This is a big advantage as a complementary pivot algorithm will take roughly eight times as longer time to solve a quadratic program than the full speed simplex-method solving a linear problem of the same size. The strategy of the approach is in the assumption that the solution of the quadratic programming problem is near the feasible point closest to the stationary point assuming no constraints.

湖北省茶叶不同气象产量方法的比较分析

基于2010—2021年湖北省夷陵区、英山县、咸安区3个茶叶主产区的茶叶产量数据,采用二次指数平滑法、HP滤波法、三年滑动平均法提取趋势产量,探究气象产量最佳提取方法,分析气候要素对茶叶气象产量的影响。结果表明:夷陵区、英山县、咸安区3个茶叶主产区的种植面积、产量、单产随着时间的推移呈多项式变化趋势,2013年之前英山县最高,2015年之后夷陵区最高;采用3种方法拟合的产量变化趋势相同,夷陵区的茶叶产量随着时间的推移呈增长趋势,而英山县和咸安区则呈减少趋势;采用二次指数平滑法和HP滤波法测算出的趋势产量均与实际产量达到显著及以上相关性,对产量剧烈波动部分有较好的捕获能力,均优于三年滑动平均法;HP滤波法得到的气象产量能较好地反映气象条件的变化,适用于湖北省3个茶叶主产区气象产量的分离,可为后续气象产量分离的研究提供参考借鉴。

决策树算法在机械臂碰撞规避方法中的应用

针对机械臂在复杂环境作业时,由于碰撞规避方法的碰撞检测效果差、障碍物规避效果不佳,导致机械臂频繁发生碰撞的问题,提出一种应用决策树算法的机械臂碰撞规避方法。通过分析机械臂运动学结构,获取机械臂运动学方程,结合二次投影法将机械臂碰撞过程,简化为三维视角下包围盒相交情况的判断过程,检测机械臂碰撞情况,通过浓度函数采集三维空间中包围盒预计位移信息,建立基于预计位移信息的决策树模型,获取机械臂碰撞规避行为最优决策信息,实现机械臂规避碰撞。实验结果表明,应用决策树算法的机械臂碰撞规避方法仅需0.29s有效检测出碰撞,在复杂环境下,规划的碰撞规避路线中机械臂与障碍物未发生碰撞,因此,该方法有效提高了机械臂碰撞规避的效果。

支撑刚度对黏弹性阻尼耗能结构的随机风振响应特性研究

针对随机风振激励下实用黏弹性阻尼耗能系统的响应分析复杂且支撑刚度影响研究不足的问题,提出了考虑安装支撑的黏弹性阻尼耗能结构的随机风振响应谱矩及方差的计算方法,并分析了支撑刚度对结构的动力响应特性。首先,依据黏弹性阻尼器与安装支撑的串联关系,建立六参数实用黏弹性阻尼器等效微分型本构方程。其次,综合运用复模态法、虚拟激励法和功率谱二次分解法,推导出耗能结构响应量(位移、层间位移、阻尼力、支撑位移)0~2阶谱矩的解析解。最后,通过算例验证了所提方法的精确性,并研究了支撑刚度对黏弹性阻尼器减震性能与结构可靠度的影响。研究表明,阻尼器支撑刚度越大,阻尼器减震性能越能得到发挥,工程应用时有必要考虑支撑刚度的不利影响。

非平稳地震激励下惯容耗能结构动力响应解析法

针对惯容减震系统在非平稳地震激励下动力响应研究不足的问题,提出设有混联Ⅰ型惯容减震系统的多自由度耗能结构动力响应时变方差的解析解法。根据惯容减震系统的本构关系、结构的动力方程及非平稳地震激励,综合利用复模态法和虚拟激励法,将惯容耗能结构解耦为一阶系统,以便获得结构位移、速度、层间剪力等响应量的统一解。采用二次式分解法将统一解的时变功率谱密度函数转化为惯容耗能结构复模态特征值、模态系数、时变模态强度系数和含有圆频率平方项的二次式乘积的线性组合。在此基础上,利用非平稳模态谱矩在无限积分区间有解析解的特征,推导出非平稳地震激励下耗能结构响应时变方差的解析解。通过采用突加型白噪声激励对结构动力响应进行分析,验证了所提动力响应功率谱和时变方差的正确性。同时,基于突加型Kanai-Tajimi模型的框架结构动力响应研究,分析了惯容系统参数对减震效果的影响。所提方法可适用于线性结构在其他非平稳调制函数的地震动下的响应分析。

科技自立自强视域下中国科技人才效能测度、区域差异及影响因素

科技人才是国际竞争的关键性战略资源,精准把握科技人才的提升潜力、准确辨析其失衡症结并探寻其平衡路径是夯实科技人才之基,下好科技创新“先手棋”的内在要求。以“东西”和“南北”差异作为切入点,采用G1-纵横向拉开档次法考察区域科技人才效能,并借助标准差椭圆、Dagum基尼系数等多样化空间分析工具揭示我国科技人才效能的时空格局及地区差异,在此基础上进一步运用关系数据分析范式探寻科技人才效能地区差异形成的影响因素。研究结果表明:我国科技人才效能具有显著的非均衡特征,空间分布上的“东高西低,南高北低”格局与时序增速上的“东慢西快,南快北慢”格局并存,且集聚重心逐渐向西南方向移动;我国科技人才效能的地区差异呈现逐年上升的演变态势,且东西方向的空间差异高于南北方向;平衡技术开放和文化教育差异是缩小整体科技人才效能差异的主要途径,不同地区差异形成的原因存在异质性。研究结果对于全面协同提升科技人才效能,扎实推进科技自立自强战略具有重要启示和现实意义。

二阶非线性抛物方程的B样条有限元法

首先,用二次B样条有限元法求解Fisher-Kolmogorov(FK)方程,证明半离散格式与全离散格式解的稳定性与收敛性;其次,用Crank-Nicolson方法离散时间变量,得到近似解的收敛阶为O((Δt)^(2)+h^(3));最后,用数值算例验证了理论分析结果及B样条有限元法的有效性.

基于压缩感知的缺失机械振动信号重构新方法

针对工业机械设备实时监测中不可控因素导致的振动信号数据缺失问题,提出一种基于自适应二次临近项交替方向乘子算法(adaptive quadratic proximity-alternating direction method of multipliers, AQ-ADMM)的压缩感知缺失信号重构方法。AQ-ADMM算法在经典交替方向乘子算法算法迭代过程中添加二次临近项,且能够自适应选取惩罚参数。首先在数据中心建立信号参考数据库用于构造初始字典,然后将K-奇异值分解(K-singular value decomposition, K-SVD)字典学习算法和AQ-ADMM算法结合重构缺失信号。对仿真信号和两种真实轴承信号数据集添加高斯白噪声后作为样本,试验结果表明当信号压缩率在50%~70%时,所提方法性能指标明显优于其它传统方法,在重构信号的同时实现了对含缺失数据机械振动信号的快速精确修复。

西鄂尔多斯绵刺及周边群落种间关联性研究

珍稀濒危植物绵刺在西鄂尔多斯地区常形成优势群落,呈小斑块状与其他群落相间分布。为了解其他植物对绵刺的影响,进而探讨种间以及群落间的关系,调查绵刺及其周边共7个群系类型14个样地,采用χ2检验、Pearson相关检验、Spearman秩相关检验对其主要物种的种间关联进行研究。结果表明:36个种组成630个种对,其中χ2检验的正负关联比为0.96;Pearson相关系数检验正负关联比为0.4;Spearman秩相关系数检验正负关联比为0.85,其检验显著率分别为35.7%、10%、31.7%,表现出种间关系较为松散。3种方法共同显示,绵刺和草本植物冠芒草呈极显著正关联(P<0.01),而与灌木霸王、小半灌木猫头刺以及草本植物刺沙蓬和画眉草呈极显著或显著负关联。

改善低次烟叶品质的生物发酵工艺优化

为改善低次烟叶吸食品质,提升烟叶可用性,优选3种酶系、菌系(蛋白多肽酶系、木质酶系、增香菌系)配制成复合生物发酵制剂,以品质改善程度为评价指标,采用单因素法和均匀设计法优化了烟叶生物发酵工艺。结果表明:(1)最佳发酵工艺条件为,发酵制剂/烟丝质量比4%、物料含水量22%、发酵温度37℃、发酵时间42 h。(2)发酵工艺各因素中,发酵温度对品质改善程度大于物料水分、发酵时间。(3)在最佳发酵条件下,烟叶品质改善程度为1.04,杂气减少、刺激性降低,感官质量大幅提升,发酵后烟叶蛋白质、淀粉、果胶、木质素分别降低9.17%、15.59%、16.67%、7.84%,醛类、酮类、醇类等物质较原样分别增加了23.70%、15.33%、41.03%。通过发酵工艺优化,烟叶化学成分更协调,烟叶可用性提升。