Optimal guidance strategy for flexible load based on hybrid direct load control and time of use

The time-of-use(TOU)strategy can effectively improve the energy consumption mode of customers,reduce the peak-valley difference of load curve,and optimize the allocation of energy resources.This study presents an Optimal guidance mechanism of the flexible load based on strategies of direct load control and time-of-use.First,this study proposes a period partitioning model,which is based on a moving boundary technique with constraint factors,and the Dunn Validity Index(DVI)is used as the objective to solve the period partitioning.Second,a control strategy for the curtailable flexible load is investigated,and a TOU strategy is utilized for further modifying load curve.Third,a price demand response strategy for adjusting transferable load is proposed in this paper.Finally,through the case study analysis of typical daily flexible load curve,the efficiency and correctness of the proposed method and model are validated and proved.

Equilibrium dividend strategies in the dual model with a random time horizon

This paper investigates the dividend problem with non-exponential discounting in a dual model.We assume that the dividends can only be paid at a bounded rate and that the surplus process is killed by an exponential random variable.Since the non-exponential discount function leads to a time inconsistent control problem,we study the equilibrium HJB-equation and give the associated verification theorem.For the case of a mixture of exponential discount functions and exponential gains,we obtain the explicit equilibrium dividend strategy and the corresponding equilibrium value function.Besides,numerical examples are shown to illustrate our results.

Performance evaluation of series and parallel strategies for financial time series forecasting

Background:Improving financial time series forecasting is one of the most challenging and vital issues facing numerous financial analysts and decision makers.Given its direct impact on related decisions,various attempts have been made to achieve more accurate and reliable forecasting results,of which the combining of individual models remains a widely applied approach.In general,individual models are combined under two main strategies:series and parallel.While it has been proven that these strategies can improve overall forecasting accuracy,the literature on time series forecasting remains vague on the choice of an appropriate strategy to generate a more accurate hybrid model.Methods:Therefore,this study’s key aim is to evaluate the performance of series and parallel strategies to determine a more accurate one.Results:Accordingly,the predictive capabilities of five hybrid models are constructed on the basis of series and parallel strategies compared with each other and with their base models to forecast stock price.To do so,autoregressive integrated moving average(ARIMA)and multilayer perceptrons(MLPs)are used to construct two series hybrid models,ARIMA-MLP and MLP-ARIMA,and three parallel hybrid models,simple average,linear regression,and genetic algorithm models.Conclusion:The empirical forecasting results for two benchmark datasets,that is,the closing of the Shenzhen Integrated Index(SZII)and that of Standard and Poor’s 500(S&P 500),indicate that although all hybrid models perform better than at least one of their individual components,the series combination strategy produces more accurate hybrid models for financial time series forecasting.

Feedback control strategy of longitudinal temperature and finished carbonization time for coke oven and its application

Based on the detailed analysis of the third coke oven in BaoSteel, a feedbackcontrol strategy of longitudinal temperature and finished carbonization time of coke ovens wasproposed and it was applied to the third coke oven in BaoSteel. As a result, the ratio of theinstance that the absolute deviation of the longitudinal temperature is within +- 7 deg C and thefinished carbonization time within +- 10 min is more than 80 percent, having acquired the patentsaving effect of an energy consumption lowered by 2.92 percent. At the same time, it can provide anexample for the same coke ovens inside and outside the nation.

Stabilization strategy of a car-following model with multiple time delays of the drivers

An extended car-following model with multiple delays is constructed to describe driver's driving behavior.Through stability analysis,the stability condition of this uncontrolled model is given.To dampen the negative impact of the driver's multiple delays(i.e.,stability condition is not satisfied),a novel control strategy is proposed to assist the driver in adjusting vehicle operation.The control strategy consists of two parts:the design of control term as well as the design of the parameters in the term.Bifurcation analysis is performed to illustrate the necessity of the design of parameters in control terms.In the course of the design of parameters in the control term,we improve the definite integral stability method to reduce the iterations by incorporating the characteristics of bifurcation,which can determine the appropriate parameters in the control terms more quickly.Finally,in the case study,we validate the control strategy by utilizing measured data and configuring scenario,which is closer to the actual traffic.The results of validation show that the control strategy can effectively stabilize the unstable traffic flow caused by driver's delays.

Is it time to rethink the Alzheimer's disease drug development strategy by targeting its silent phase?

Alzheimer＇s disease （AD） is the most frequent cause of dementia in the western world. In clinical terms, AD is characterized by progres- sive cognitive decline that usually begins with memory impairment. As the disease progresses, AD inevitably affects all intellectual functions including executive functions, leading to complete dependence for basic activities of daily life and premature death.

Stable attenuation-compensated reverse time migration and its application to land seismic data

Intrinsic attenuation of the earth causes energy loss and phase distortion in seismic wave propagation.To obtain high-resolution imaging results,these negative effects must be considered during reverse time migration(RTM).We can easily implement attenuation-compensated RTM using the constant Q viscoacoustic wave equation with decoupled amplitude attenuation and phase dispersion terms.However,the nonphysical amplitude-compensation process will inevitably amplify the high-frequency noise in the wavefield in an exponential form,causing the numerical simulation to become unstable.This is due to the fact that the amplitude of the compensation grows exponentially with frequency.In order to achieve stable attenuation-compensated RTM,we modify the analytic expression of the attenuation compensation extrapolation operator and make it only compensate for amplitude loss within the effective frequency band.Based on this modified analytic formula,we then derive an explicit time-space domain attenuation compensation extrapolation operator.Finally,the implementation procedure of stable attenuation-compensated RTM is presented.In addition to being simple to implement,the newly proposed attenuation-compensated extrapolation operator is superior to the conventional low-pass filter in suppressing random noise,which will further improve the imaging resolution.We use two synthetic and one land seismic datasets to verify the stability and effectiveness of the proposed attenuationcompensated RTM in improving imaging resolution in viscous media.

An Analysis of the Pre-writing Strategies Employed by Chinese College Students in the Timed Examination

This thesis is trying to analyze the pre-writing strategies used by Chinese college students in a timed examination.The purposes of this study is to identify the possible strategies the Chinese college students claimed they used in the pre-writing stage of the timed examination,find if differences exist between the pre-writing strategies employed by skilled writers and unskilled writers,and find which strategy best facilitate writing in a timed condition.

中国体育产业数字化转型的时代逻辑、问题审视及应对方略

面对百年未有之大变局,数字技术赋能经济社会高质量发展已是大势所趋,同时也为体育产业的数字化转型升级带来了新思路、新方向和新动力,对全面落实体育强国、健康中国以及全民健身等国家战略具有重大意义。运用文献资料等方法,对体育产业数字化转型的时代逻辑、问题审视以及应对方略进行探讨。研究认为,产业数字化浪潮的不可逆转、体育产业高质量发展的时代呼唤以及体育消费转型升级的形势倒逼是中国体育产业数字化转型的时代逻辑。立足体育政策落实、体育市场动力、体育服务消费、体育技术应用等层面对中国体育产业数字化转型进行问题审视,并在此基础上提出健全政策保障体系、创新企业发展模式、培养数字消费群体、深化数字技术应用等推进中国体育产业数字化转型的应对方略。

煤矸分拣多机械臂任务分配问题研究

针对煤矸分拣过程中分拣率低、大粒度矸石分拣效果差等问题,通过考虑矸石粒度、分拣时间、矸石与分拣区边界距离等因素,构建矸石优先级模型;采取分拣机械臂放置矸石后不复位的方式,提出了一种煤矸分拣多机械臂任务分配策略,并以分拣率为标准进行评判,最后,采用本研究分配策略和传统的分配策略进行仿真。结果表明:本研究分配策略比传统的分配策略分拣效果更好,提高了7%~10%的分拣率,减少了大粒度矸石的漏拣数量;当矸石的间距不变时,矸石数量变化对分拣率影响较小,分拣率波动在3%左右,验证了本研究分配策略的有效性;矸石间距对分拣率和分拣机械臂数量的影响较大,当矸石的间距增大时,分拣率得到提高;矸石间距在250 mm以上时,3个分拣机械臂能保证较高的分拣率。

基于遗传算法的时间敏感网络调度方法

随着网络技术的进步,车载网、工业物联网以及5G超高可靠低时延通信(uRLLC)等应用都需要时间敏感网络(TSN)来保证超低延时的确定性数据传输。TSN流量调度需要快速且精确的调度算法,现有的精确式求解方法复杂度高,在大规模联合调度时无法满足实时性。文中设计了一种性能更优的路由优化遗传算法(Routing-GA),结合路由和流量调度约束,能通过优化路由来提高调度算法求解效率,为链路负载均衡调度提供服务。该策略增加了调度的求解空间以及求解灵活性,具备元启发式算法的快速求近最优解特点,能够简单有效地处理大规模TSN路由约束联合调度问题。Routing-GA以时间敏感流最小端到端时延作为优化目标,联合考虑路由和TSN约束,并针对TSN传输问题特性提供一种低复杂度、高效率和高拓展性的遗传算法编码方式。此外,为了提高调度算法的性能,提出针对路由长度及链路负载均衡进行优化的交叉变异机制。实验结果表明所实现的Routing-GA能有效减少端到端时延,显著提高求解质量,进化率可以达到24.42%,平均只需要传统遗传算法(GA)迭代运行时间的12%,从而有效提高了算法的求解性能,满足TSN调度的约束要求。

基于滑模自适应有限时间一致性算法的微电网二次控制

随着微电网规模日益增大,如何快速稳定完成二次控制目标是一个亟待解决的问题。因此首先针对现有微电网中分布式二次控制器的收敛速度问题,提出了一种基于自适应有限时间的分布式二次控制,所提的控制器在不同的场景下,可以通过分布式的方式来获取当前情况下最适合的有限时间控制器的收敛系数,从而加快二次控制的速度。其次针对分布式控制器易受到扰动而无法完成控制目标的问题,设计了基于滑模控制的分布式有限时间控制器来消除扰动影响。然后通过李雅普诺夫函数证明方法分析了所提策略的稳定性和可行性。最后通过MATLAB/Simulink搭建仿真模型,在4个不同的算例下验证了本文所提的控制策略的有效性和可行性。

基于多时间尺度的户用光储能量管理策略

针对光伏出力的波动导致户用光储系统能量优化不确定性的问题,提出了一种多时间尺度能量管理策略。在日前阶段,综合考虑分时电价、储能系统的寿命和负荷的可控性,建立了以用户用电成本、储能运行成本和环境成本最小化为目标的调度模型;在日内阶段,基于模型预测控制(model prediction control,MPC)并参考日前调度计划进行实时调度能量优化,矫正光伏出力的预测偏差,在不影响用户舒适度的前提下降低系统运行成本。最后,仿真结果验证了所提能量管理策略的经济性和有效性。

基于改进A*算法的多AGV路径规划及避障研究

针对多自动导引运输车(automated guided vehicle,AGV)路径规划与避障问题,考虑AGV行驶中启、制动速度与转弯角度对行驶时间的影响,根据不同冲突类型制定避障策略,以所有AGV行驶总时间最短为目标,建立多AGV路径规划与避障模型,并设计改进A*算法进行求解。对两组数量不同的多AGV进行路径规划与避障仿真,结果表明:相较于一般A*算法,基于改进A*算法的多AGV路径规划及避障总时间优化率分别为10.0%和10.5%,总路径长度优化率分别为7.1%和7.8%。与其他改进智能算法的进一步比较证实,改进A*算法在缩短路径规划用时和路径长度方面具有明显优势。本文提出的改进A*算法可高效地规划出多AGV运行的无碰撞路径,其改进思路也贴切反映了AGV的实际运行工况。

光流结合特征提取的室内机器人避障技术研究

为解决室内机器人正向准确避障问题,提出一种光流结合特征提取的视觉避障方法。将LK光流与多尺度思想结合,加入仿射变换,提高算法追踪角点的噪声鲁棒性,进而准确检测视场中的障碍物;通过评估障碍物风险程度,制定出碰撞时间(TTC)结合光流平衡策略的碰撞机制,引导机器人在无碰路径上移动。改进光流与特征提取结合能提高相机快速运动下的追踪成功率,制定的碰撞策略能够有效规避机器人前方的障碍物。实验表明,相机快速运动时,算法能提高追踪的准确性,有效检测出视场中的障碍物,引导机器人无碰撞行驶,具备较强的独立性和实时性。

我国社会体育指导员制度实施30年:历程、意蕴与完善

我国社会体育指导员制度是改革开放后较早建立的体育制度,至今已实施30年。30年来,随着经济社会和体育事业发展,该制度不断调整和优化,对中国式体育现代化和全民健身发展发挥了重要作用,提供了基础性的工作支撑和规范保障。为做好该制度实施的总结思考和进一步推进的发展探讨,将制度发展历程划分为3个阶段,并描述概括其发展样态;从多个视角探究制度发展的多元推进动力与深刻时代意涵;进而从直面难题提升治理、落实《体育法》完善配套和解决各类社会体育指导员工作发展突出问题等重点方面,针对面临的各种现实需求与挑战,提出进一步发展完善该制度的应对方策。

国家知识产权战略对高技术产业创新效率的影响——基于时间断点回归设计

在我国从知识产权大国向知识产权强国迈进的关键时期,探究实行国家知识产权战略对高技术产业创新效率的影响,既是推动高技术产业升级的有效手段,也是改革完善知识产权保护与管理制度的内在需求。基于2000—2019年中国28个省市地区高技术产业创新数据,运用时间断点回归方法检验中国实施国家知识产权战略对高技术产业创新效率的影响。研究表明:国家知识产权战略的实施在整体上显著促进高技术产业创新效率提升。区域异质性分析发现,战略实施显著提升了东、西部地区高技术产业的创新效率,但对中部地区创新效率的提升作用不显著。研究结论为优化知识产权政策设计、提高高技术产业的创新能力提供了经验证据。未来应进一步健全知识产权制度体系,并结合区域差异因地制宜制定知识产权政策。

中国式现代化进程中冰雪运动跨越式发展的时代机遇、战略任务与推进方略

采用文献资料法、逻辑分析法、专家访谈法等方法,全面阐述中国式现代化进程中冰雪运动跨越式发展的时代机遇、战略任务与推进方略。研究认为,中国式现代化的5个基本特征为冰雪运动跨越式发展提供了与之相对应的参与基础、经济支撑、发展方向、原则遵循、交流空间等时代机遇。冰雪运动跨越式发展的主要战略任务为推动群众冰雪运动深入开展、健全竞技冰雪运动发展平台、激发冰雪产业市场竞争活力等。从群众体育、竞技体育、体育产业等3个方面,提出推广普及冰雪运动、提升竞技冰雪运动实力、加快冰雪产业转型升级等我国冰雪运动跨越式发展的推进方略。

基于新型细菌觅食优化算法的飞机动态泊位问题

随着航空运输业的发展,传统手动设计泊位方案已难以满足日益增长的外包维修需求.在外包模式下,如何快速给出高效的动态泊位方案关系到维修任务订单的准点交付,是飞机维修服务公司亟待解决的重要问题.针对飞机泊位进出顺序及碰撞检测特点,构建带时间窗的飞机维修泊位模型.设计自适应趋化学习及交叉协作策略,提出新型细菌觅食优化算法,并设计一系列约束处理机制.研究结果表明,提出的基于矩形碰撞检测方法可有效预防并判断飞机间碰撞阻塞情况.新型细菌觅食优化算法在解决飞机动态泊位问题上展现出搜索精度高、稳定性强等特点.所得高效智能化泊位调度方案有助于在保证维修安全的情况下提升飞机维修服务提供商的维修服务效率,改进维修资源利用率与维修系统的柔性,为企业实现高质量发展打下良好基础.

改进遗传算法搜索动态订单下车辆路径最优问题

滚动周期策略是当前学者利用优化算法解决动态车辆路径规划(dynamic vehicle routing planning,DVRP)问题的主要研究策略。预优化算法是基于遗传算法(genetic algorithm,GA)进行改进。GA易早熟和易陷入局部最优的特点,使解的质量往往不能达到最好。针对此问题,在GA算法上提出了贪婪重构策略进行改进。贪婪重构遗传算法(greedy reconstruction genetic algorithm,GRGA)随机剔除每条路径固定数量的客户点,利用贪婪重构策略依次将剔除点插入到各个路径,保留成本最低的解,摒弃了完全随机的策略原则,使解可以跳出局部最优。在每次迭代之后利用变邻域下降搜索算法(variable neighborhood descent,VND)进行深度搜索,完成一次迭代。最后进行三组测试,第一组是在统一平台上采用Solomon数据集测试算法效果,第二组是把预优化改进算法与对比算法得到的数据分别进行保存,利用控制变量法在动态调度周期使用一种动态调度优化算法,分别对每个预优化算法形成的初始路径进行调度,测试改进算法的有效性,第三组是采用实际案例测试预优化算法的效果。