MOORE-PENROSE INVERSE SIMPLEX ALGORITHMS BASED ON SUCCESSIVE LINEAR SUBPROGRAMMING APPROACH

Generalized simplex variants based on successive linear subprogramming approach (SLS) are described in this paper. In stead of inverse matrix, these variants employ Moore-Penrose inverse. They are respectively characterized by different pivoting rules, Numerical results of limited tests show encouraging performance of these variants.

Successive quadratic programming multiuser detector

Based on the semidefinite programming relaxation of the CDMA maximum likelihood multiuser detection problem, a detection strategy by the successive quadratic programming algorithm is presented. Coupled with the randomized cut generation scheme, the suboptimal solution of the multiuser detection problem in obtained. Compared to the interior point methods previously reported based on semidefmite programming, simulations demonstrate that the successive quadratic programming algorithm often yields the similar BER performances of the multiuser detection problem. But the average CPU time of this approach is significantly reduced.

A SUCCESSIVE QUADRATIC PROGRAMMING ALGORITHM FOR SDP RELAXATION OF MAX-BISECTION

A successive quadratic programming algorithm for solving SDP relaxation of Max- Bisection is provided and its convergence result is given. The step-size in the algorithm is obtained by solving n easy quadratic equations without using the linear search technique. The numerical experiments show that this algorithm is rather faster than the interior-point method.

Local vs. cross station simulation of suspended sediment load in successive hydrometric stations: heuristic modeling approach

The present paper aims at modeling suspended sediment load(SSL) using heuristic data driven methodologies, e.g. Gene Expression Programming(GEP) and Support Vector Machine(SVM) in three successive hydrometric stations of Housatonic River in U.S. The simulations were carried out through local and cross-station data management scenarios to investigate the interrelations between the SSL values of upstream/downstream stations. The available scenarios were applied to predict SSL values using GEP to obtain the best models. Then, the best models were predicted by SVM approach and the obtained results were compared with those of GEP. The comparison of the results revealed that the SVM technique is more capable than the GEP for modeling the SSL through the both local and cross-station data management strategies. Besides, local application seems to be better than cross-station application for modeling SSL. Nevertheless, the cross-station application demonstrated to be a valid methodology for simulating SSL, which would be of interest for the stations with lack of observational data. Also, the prediction capability of conventional Sediment Rating Curve(SRC) method was compared with those of GEPand SVM techniques. The obtained results revealed the superiority of GEP and SVM-based models over the traditional SRC technique in the studied stations.

Transcontinental Translational Medicine Collaboration: A Successful SinoCuban Joint B-to-B Program

Translational medicine is a comprehensive discipline that aims to convert laboratory research results into products and technology for clinical application using modern molecular biological techniques, to improve our understanding of the human body and disease and to optimize laboratory design for clinical observation and analysis for basic research. Its ultimate goal is improving holistic medicine and helping patients solve their health problems. Translational medicine includes two processes： bench to bedside and bedside to bench, known as B-to-B processes. The first B-to-B （bench to bedside） refers to the application of results of the laboratory to clinical use as a medical product or a diagnosis and treatment technology. The second B-to-B （bedside to bench） describes the process by which clinical observation and analysis provides ideas and guidance for experiment design for basic medical research. The two processes complement each other and constitute the two-way cycle of translational medicine. Translational medicine can be applied to clinical disease detection in the form of new biomarkers and can accelerate drug discovery. In recent years, with the biotechnology, increasing rapid development of outcomes of research on molecular pathogenesis can be directly applied to clinical theraDv.

Incremental Computation of Success Patterns of Logic Programs

A method is presented for incrementally computing success patterns of logic programs. The set of success patterns of a logic program with respect to an abstraction is formulated as the success set of an equational logic program modulo an equality theory that is induced by the abstraction. The method is exemplified via depth and stump abstractions. Also presented are algorithms for computing most general unifiers modulo equality theories induced by depth and stump abstractions.

An SQP algorithm for mathematical programs with nonlinear complementarity constraints

In this paper, we describe a successive approximation and smooth sequential quadratic programming （SQP） method for mathematical programs with nonlinear complementarity constraints （MPCC）. We introduce a class of smooth programs to approximate the MPCC. Using an 11 penalty function, the line search assures global convergence, while the superlinear convergence rate is shown under the strictly complementary and second-order sufficient conditions. Moreover, we prove that the current iterated point is an exact stationary point of the mathematical programs with equilibrium constraints （MPEC） when the algorithm terminates finitely.

考虑智能软开关接入的主动配电网扩展规划方法

柔性互联装置的广泛应用给主动配电网(active distribution network,ADN)规划带来巨大挑战。该文提出一种考虑智能软开关(soft open point,SOP)接入的ADN扩展规划方法,对变电站新建及扩容,线路新建,智能软开关、分布式电源、储能系统以及无功补偿等设备的选址定容进行协同规划。首先,考虑分布式电源出力和负荷功率不确定性,采用基于改进高斯混合模型的聚类方法构建典型日场景。在此基础上,以年综合费用最小为目标函数,建立了考虑SOP接入的ADN扩展规划模型。然后,通过线性化和二阶锥松弛技术,将原始非凸非线性规划模型转化为混合整数二阶锥规划(mixed-integer second-order cone programming,MISOCP)模型,并提出逐次收缩凸松弛算法以获得凸松弛间隙足够小的原问题最优解。最后,在54节点主动配电网算例上验证了所提规划模型和求解算法的可行性与有效性。

等再入航程返回轨道模糊混合优化设计

为了消除采用梯度迭代求解算法求解再入弹道优化问题时对初始值的依赖,减小遗传算法对种群数量和迭代次数的需求,采用模糊思想设计了改进的稳态遗传-序列二次规划(GA-SQP)混合求解算法。针对等再入航程返回轨道设计问题,提出了初始种群的基因检测方法、基于模糊隶属度的评分函数建立方法和搜索过程中劣质基因的评分方法,考虑了过载超限时间约束、倾侧角翻转最大角速度限制等实际约束,给出了序列二次规划求解过程中再入点在瞄准点之后和制动时长过短的特殊情况下约束的处理方法。采用改进的稳态GA-SQP混合求解算法,可以实现近地轨道变高度返回的情况下等再入航程返回轨道设计。改进的稳态GA-SQP混合求解算法不依赖于初始值,种群数量较小,与未改进的遗传-序列二次规划算法相比迭代次数减少34.7%,计算速度和计算精度均达到工程适用程度。

Successive MISOCP Algorithm for Islanded Distribution Networks with Soft Open Points

An optimal operation scheme is of great significance in islanded distribution networks to restore critical loads and has recently attracted considerable attention.In this paper,an optimal power flow(OPF)model for islanded distribution networks equipped with soft open points(SOPs)is proposed.Unlike in the grid-connected mode,the adequacy of local power generation in distribution networks is critical for islanded systems.The proposed approach utilizes the power output of local distributed generations(DGs)and the benefits of reactive power compensation provided by SOPs to allow maximum loadability.To exploit the available resources,an optimal secondary droop control strategy is introduced for the islanded distribution networks,thereby minimizing load shedding.The formulated OPF problem is essentially a mixed-integer nonlinear programming(MINLP)model.To guarantee the computation efficiency and accuracy.A successive mixed-integer second-order cone programming(SMISOCP)algorithm is proposed for handling the nonlinear islanded power flow formulations.Two case studies,incorporating a modified IEEE 33-bus system and IEEE 123-bus system,are performed to test the effectiveness of the proposed approach.

On filter-successive linearization methods for nonlinear semidefinite programming

In this paper we present a filter-successive linearization method with trust region for solutions of nonlinear semidefinite programming. Such a method is based on the concept of filter for nonlinear programming introduced by Fletcher and Leyffer in 2002. We describe the new algorithm and prove its global convergence under weaker assumptions. Some numerical results are reported and show that the new method is potentially effcient.

呼吸机依赖患者脱机尝试进程中介入抗阻力干预对脱机成功率及焦虑情绪的影响

目的探讨呼吸机依赖患者脱机尝试进程中介入渐进性抗阻力干预方案指导对脱机成功率以及焦虑情绪的影响。方法借助随机数字表法将本院ICU科室2019至2020年收治的80例呼吸机依赖患者分为对照组和研究组,每组40例,对照组脱机尝试进程中接受常规护理,研究组脱机尝试进程中加用渐进性抗阻力干预,观察2组脱机时间、一次脱机成功率、脱机成功率、并发症情况,护理前后汉密尔顿焦虑量表(HAMA)、汉密尔顿抑郁量表(HAMD)和MRC肌力评分。结果研究组脱机时间、并发症率低于对照组(P<0.05),一次脱机成功率、脱机成功率均高于对照组(P<0.05)。2组患者护理前HAMA、HAMD评分、MRC评分比较,差异无统计学意义(P>0.05),护理后研究组HAMA、HAMD评分低于对照组,MRC评分高于对照组,差异均有统计学意义(P<0.05)。结论将渐进性抗阻力干预应用到呼吸机依赖患者脱机工作中,可有效缓解其焦虑、抑郁情绪对脱机工作带来的不良影响,缩短脱机时间,提高脱机成功率,减少并发症发生的同时,改善肌力水平。

User scheduling and power allocation for downlink multi-cell multi-carrier NOMA systems

In Non-Orthogonal Multiple Access(NOMA),the best way to fully exploit the benefits of the system is the efficient resource allocation.For the NOMA power domain,the allocation of power and spectrum require solving the mixed-integer nonlinear programming NP-hard problem.In this paper,we investigate user scheduling and power allocation in Multi-Cell Multi-Carrier NOMA(MCMC-NOMA)networks.To achieve that,we consider Weighted Sum Rate Maximization(WSRM)and Weighted Sum Energy Efficiency Maximization(WSEEM)problems.First,we tackle the problem of user scheduling for fixed power using Fractional Programming(FP),the Lagrange dual method,and the decomposition method.Then,we consider Successive Pseudo-Convex Approximation(SPCA)to deal with the WSRM problem.Finally,for the WSEEM problem,SPCA is utilized to convert the problem into separable scalar problems,which can be parallelly solved.Thus,the Dinkelbach algorithm and constraints relaxation are used to characterize the closed-form solution for power allocation.Extensive simulations have been implemented to show the efficiency of the proposed framework and its superiority over other existing schemes.

基于不完全信息视角的博士研究生招考方式分析

博士研究生教育是国家人才培养的重中之重,博士研究生招考环节是博士研究生教育质量得以保障的第一道关卡。运用信息经济学理论,分析本科直博、硕博连读、公开招考三种不同招考方式所面临的信息非对称性问题,并尝试提出解决方案。结合我国国情,对于本科直博,建议完善本科生科研能力的提前培养机制,方便目标导师对报考学生的考察;对于硕博连读,建议改进硕士研究生培养环节的管理机制,促进目标导师和报考学生的相互了解;对于公开招考,建议完善推荐信内容和提交方式,客观揭示报考学生的科研能力。研究结果有助于推进博士研究生选拔体系改革,改善博士研究生培养质量,提升国家核心竞争力。

程序化急救护理在急诊危重症患者中的应用效果及对抢救成功率的影响

目的探讨程序化急救护理在急诊危重症患者中的应用效果。方法根据护理方式的不同将2020年8月至2021年8月于本院急诊科接受救治的50例危重症患者分为对照组(25例,常规急救护理)和观察组(25例,程序化急救护理)。比较两组的护理效果。结果观察组的急救时间、急诊室停留时间均短于对照组,抢救成功率、满意度均高于对照组(P<0.05)。护理后24 h,观察组的急性生理功能和慢性健康状况评分系统Ⅱ(APACHEⅡ)、格拉斯哥昏迷量表评分(GCS)以及急诊严重指数(ESI)评分均优于对照组(P<0.05)。护理后3个月,观察组的健康状况调查表(SF-36)各维度评分均显著高于对照组(P<0.05)。结论程序化急救护理可有效缩短急诊危重症患者的急救时间,提高抢救成功率,提升生活质量。

A NEW SUCCESSIVE QUADRATIC PROGRAMMING ALGORITHM

The main difficulties encountered in the successive quadratic programming methods are.the choice of penalty parameter, the choice of steplenth, and the Maratos effect. An algorithmwithout penalty parameters is presented in this paper. The choice of steplength parameters isbased on the method of trust region. Global convergence and local superlinear convergence areproved under suitable assumption.

一种在线电力系统静态稳定增强控制算法

提出了一种在线应用的电力系统静态稳定增强控制算法。这一算法基于连续线性规划技术,将增强控制问题分解为稳定临界点及其控制灵敏度的计算问题和基于灵敏度的优化控制问题。在前一个子问题中,运用基于连续潮流的间接方法分别计算得到每个故障的稳定临界点。在后一个子问题中,采用了参与控制集和部分变量的可控区间限制等策略来提高线性规划问题的计算有效性。一个3000 节点的实际系统的应用表明,文中所提算法是有效实用的。

一种基于连续线性规划的静态稳定预防控制方法

针对故障后不存在静态稳定平衡点的严重失稳故障,提出了一种静态稳定预防控制算法。该方法基于连续线性规划技术,将预防控制问题分解为故障参数空间上虚拟稳定临界点及其控制灵敏度的计算子问题和基于灵敏度的线性规划控制子问题。在前一个子问题中,运用故障连续潮流工具分别计算得到每个失稳故障的虚拟稳定临界点;在后一个子问题中,采用了筛选参与控制集和限制可控区间等策略来提高线性规划问题计算的有效性。对国外一个3000节点的实际系统的应用表明了所提出的算法是有效、实用的。

水库调度图优化研究

应用动态规划法,结合具体实际,建立相应的数学模型,对水库调度图进行优化.以隔河岩水库为例,在满足系统运行可靠性要求和各种约束条件下,迭代计算确定出水库优化调度图;并求得在优化调度图下水库运行各种参数和动能指标.通过指标对比,验证了模型和算法的有效性和可行性,具有生产应用价值.

基于连续线性规划的梯级水电站优化调度

梯级水电站优化调度是一个多时段、多变量和多约束条件的大规模优化问题,其求解过程非常复杂。文章尝试采用连续线性规划的优化方法来解决梯级水电站长期优化调度问题。通过采用泰勒级数一阶描述形式,对优化调度目标函数和约束条件中的非线性约束进行线性化处理,建立了基于连续线性规划算法的优化调度数学模型,提出了用连续线性规划技术求解梯级水电站优化调度问题的算法,并采用迭代步长的动态比例缩减因子保证算法能快速准确地收敛到优化问题的最优解。利用Matlab7.0编制连续线性规划梯级水电站优化调度程序,一个两级梯级水电站群的仿真分析结果表明,该算法可用于求解梯级水电站优化调度问题,并可快速得到非线性问题的最优解。