Jeffcott转子系统分岔点预测

首先简述了一种用于转子轴承系统的稳定性量化分析方法,即首先利用数值积分对高维非线性转子系统进行解耦,将Rn轨线映射为一系列R1映像轨线,然后在R1观察空间中定义轨线的稳定裕度,根据轨线稳定裕度利用灵敏度技术预测动力系统的分岔点。最后,对一个单跨转子模型试验台建立了动力学方程,并利用上述方法通过2个算例预测了系统发生分岔的参数值和分岔特性。预测结果与直接数值积分法在庞加莱截面得到的分岔参数值基本一致,但由于该方法利用了灵敏度技术,所以其分岔点的搜索过程比直接数值积分法中的试探法要快得多。     

灰色神经网络模型应用于证券短期预测研究

证券市场中存在大量的非线性及混沌现象使得许多基于证券投资理论建议的各种线性模型在对其发展进行预测时往往得不到很好的结果。利用两种非线性预测模型并充分考虑各技术指标之间的序列相关性,在灰色GM(1,1)预测模型的基础上提出了组合灰色神经网络预测模型。通过对近期深证成指及首钢股份进行短期预测和检验,结果表明了该方法具有很高的精确度及广泛的应用前景。     

具有异质预期类型和产品的差异度的Cournot 博弈动力学分析与控制

本文通过构建具有异质预期的企业寡头博弈模型, 分析了产量竞争下的纳什均衡局部稳定性。 研究表明基于边际利润和一个适应性预期的决策参数, 企业遵循一个梯度的规则, 决定了纳什均衡的局部稳定性, 产品差异化的程度对稳定性的影响取决于产品的性质。 此外, 时滞反馈控制可以控制动力系统的混沌行为且数值分析表明其可高效、 快速的控制动力系统的不稳定行为, 使得市场快速恢复稳定、有序的状态, 为决策者提供有效解决市场不稳定现象的方法。     

钻井柴油机非正常运转预防装置及应用

针对机械钻机动力系统出现意外故障情况下,受外力驱动非正常运转的现象,开发了一种预防装置,装置由油控阀和管线连接组成,安装方便,能保证钻井柴油机的正常使用和操作,防止因柴油机被动运转可能导致的恶性事故发生,减少设备故障对生产造成的影响,保证柴油机安全运行。     

一种新的非线性系统电路及同步设计

基于Chen系统设计一种新的多翅膀混沌系统.在z方向上对系统进行改进,扩展其鞍焦平衡点,通过偶对称多分段平方函数控制系统,得到多翅膀吸引子.根据Matlab仿真得到理论相图,利用Multisim软件进行电路设计得到数值仿真相图,二者相互吻合,证实了系统的正确性和可实现性.通过求解混沌系统的分岔图和最大Lyapunov指...     

进出口总额时间序列的混沌特性分析及其预测

混沌时间序列分析方法为进出口总额这类经济时间序列分析提供了一种新的工具,论文建立了小数据量时间序列混沌特征分析方法和基于径向基函数神经网络的预测模型,并应用到进出口总额时间序列混沌分析和非线性预测,获得了较好的预测效果.     

管理“精细”化 设备更“听话”

上海石化不断加强设备管理,以提高生产装置稳定、长周期运行水平为重点,结合节能减排和系统优化工作,不断提升公司设备动力系统管理能力和水平。随着管理"精细"化,设备更"听话"了:今年1～4月因设备故障引起装置非     

基于耗散结构论的中国公司治理研究

公司治理作为人类经济社会中一个开放型系统,其基本构件--各个子系统序参量变化,可不断地产生高阶有序跃迁,进而引发治理系统形成新的稳态耗散结构.其耗散机理主要表现为远离平衡状态的非线性和非稳定性,状态序参量在开放态下的变动方向、速率和跃迁水平,耗散跃迁的对称性自发破缺及分岔,微涨落的非线性放大和非平衡相变.中国公司治理必须完善其构件的开放性及其交互效应,形成耗散结构的高阶有序跃迁,优化结构,完善功能,达到"无为而治"的高度境界.     

苯乙烯装置P3003汽提塔釜液泵故障分析及对策

苯乙烯装置P3003汽提塔釜液泵是苯乙烯装置的主要设备,该泵的平稳运行与否,对装置有较大影响。本装置P3003汽提塔釜液泵在运行中出现过滤网堵塞、电机经常超电流等故障,需要频繁维修,影响了装置的平稳运行。中国同类装置也出现过相同现象,因此文章针对P3003汽提塔釜液泵故障现象进行了分析,找出了故障的根本原因,并针对故障原因进行了改造。以期为同行进行借鉴。     

基于混沌蚁群算法的SVM模型在水库枯水期径流预测中的应用

本文采用混沌蚁群算法对SVM模型的参数进行优化计算,并采用高斯核函数对模型进行混沌特性识别,简化模型在枯水期径流预测非线性求解过程。结合优化模型对水库枯水期径流进行预测。研究结果表明:基于混沌蚁群算法的SVM模型可较好的辨识复杂的水文序列,模型具有较高的泛化能力,相比于传统算法,水库枯水期径流预测精度得到明显改善,具有较高的适用性。研究成果对于水库枯水期径流预测提供方法参考。     

Understanding success and failure in customer relationship management

Customer Relationship Management (CRM) systems can help organizations manage customer interactions more effectively. Like many new technologies, CRM has been accompanied by vendor hype and stories of implementation failure. Work on critical success factors (CSFs) should encourage more appropriate implementation practice; however many CSF studies conclude with a list of factors but provide little further guidance. In particular, there is a need for stronger theoretical models of the entire CRM innovation process which can be used by managers to understand better the underlying causes of success and failure. This paper adopts a novel approach to this problem by firstly developing a conceptual model of CRM innovation and then converting this model into a dynamic simulation model. Some early simulation results illustrating changes in CRM benefits and organizational support over time are presented together with a discussion of the underlying causes and suggestions for how managers can counteract potential innovation failure.     

农机自动驾驶设备作业检测系统的设计与实现

为了满足精准农业领域对农机自动驾驶系统作业进行性能评估和质量管控的需求,解决常规人工测量中误差大、不确定度高的难题,设计一种在真实作业环境中使用的高精度检测系统,使用组合导航系统为核心组件搭建硬件采集设备,运用动态后处理技术(PPK)对观测数据进行深耦合处理,并开发基于JavaScript的自动化评估软件,实现检测过程...     

The science of complexity: An alternative perspective for strategic change processes

The two perspectives of strategy process most firmly established in the literature—strategic choice and ecology—assume the same about system dynamics: negative feedback processes driving successful systems (individual organizations or populations of organizations) toward predictable equilibrium states of adaptation to the environment. This paper proposes a third perspective, that of complex adaptive systems. The framework is provided by the modern science of complexity: the study of nonlinear and network feedback systems, incorporating theories of chaos, artificial life, self-organization and emergent order. Here system dynamics are characterized by positive and negative feedback as systems coevolve far from equilibrium, in a self-organizing manner, toward unpredictable long-term outcomes.     

Exploring the internal and external venturing of large R&D-intensive firms

We explore the realized strategies of large R&D-intensive firms through a venturing lens, focusing on two industries: pharmaceuticals and high-technology equipment manufacturing. Specifically, we examine changes in strategy over time along two critical dimensions: (1) focus of venturing, i.e., internally vs externally oriented, and (2) learning orientation i.e., explorative vs exploitative. Our empirical analysis is based on news stories relating to six large, R&D-intensive firms over a 6-year period. The findings suggest the following: (1) exploration is more prevalent than exploitation in both pharmaceuticals and high-technology equipment manufacturing, but pharmaceuticals have a greater preference for internal venturing than high-technology equipment manufacturing; (2) three firm-level venturing strategy types can be discerned, which are independent of the specific industry; and (3) change in realized strategy is a dynamic capability facilitated by firm-level factors. These results, albeit explorative, emphasize venturing in R&D industries as a dynamic capability that is influenced by firm-level characteristics rather than industry membership.     

Automatic production control applying control theory

A new dynamic production model for the planning level will be presented in this paper. The model is based on methods of control theory, which provide a large variety of appropriate tools for analysing and controlling dynamic systems. With the help of the funnel model and the theory of the logistic operating curve, a continuous flow model of a single work centre has been designed. For the control task a backlog controller and a WIP controller have been developed. The controllers interact to adjust the capacity and the input rate of the work centre so as to eliminate the backlog as soon as possible and to set the WIP to a defined level. By means of envelope curves of capacity flexibility, which are easily applicable to industry, the individual range of capacity adjustments at a single work centre can be modelled. Simulation experiments confirm that this concept ensures the synchronisation of capacity and work. The objective is to develop a closed-loop control for PPC with defined control and reference variables based on the logistical objectives.     

Monetäre Anreize zur Steuerung der Ladelast von Elektrofahrzeugen – eine modellgestützte Optimierung

Electric mobility is supposed to contribute to climate policy targets by reducing CO₂-emissions in the transportation sector. Increasing penetration rates of electric vehicles (EV) can lead to new challenges in the electricity sector, especially with regard to local distribution networks. Thus the management of charging loads is discussed as a key issue in energy economics. Due to their long parking times, high electricity and power demand, EV seem to be predestined for load management. Monetary incentives as dynamic pricing can be suitable for that: They reflect the current supply situation, pass the information to the consumers and can thus lead to a corresponding charging behaviour. In this article we analyse this interaction between dynamic pricing and charging loads. For this reason we have developed the optimization model DS-Opt+. It models a total number of 4,000 households in two residential areas of a major city with regard to its electricity demand, its mobility behaviour and its equipment of photovoltaic systems. Four different pricing models are tested for their effects on charging behaviour and thus the total load of the residential area. The results illustrate that only fairly high penetration rates of EV lead to remarkably higher electricity demand and require some load management. The tested dynamic pricing models are suitable for influencing charging loads; load-based tariffs are best in achieving a balanced load curve. In our analysis uncontrolled charging strategies are superior regarding a balanced load curve than controlled strategies by time-varying tariffs. Our results lead to several implications relevant for the energy industry and further research.     

基于改进AG算法的机器人动态路径规划方法

为了充分发挥Agoraphilic(AG)算法的优越性,使其可以在动态环境中有效地进行路径规划,对传统AG算法进行了研究和改进,在计算自由空间力时增加了机器人和动态障碍物之间的相对速度分量,该分量可分解为2个方向的分力,一个分力使机器人向背离障碍物的方向运动,另一个分力使机器人向垂直于障碍物的方向运动,充当机器人绕行的动力。利用Matlab进行了仿真实验,将改进的AG算法和几种其他动态路径规划方法进行了对比。改进后的AG算法使机器人能够迅速躲避动态障碍物,有效地进行动态避障。研究方法不仅可以解决动态环境中机器人躲避动态障碍物并到达目标点的问题,而且与其他动态路径规划算法相比,具有路径长度更短、耗时更少、路径更平滑等优点。     

基于商场冷负荷特点的多台冷水机组优化配置研究

针对商场的热量特点讨论了约束条件和影响因子,模拟了动态冷负荷变化规律,给出了多台冷水机组优化配置方法及商场空调系统优化方案,并与原静态冷负荷法设计的空调系统进行对比分析,发现可节约36%左右的机组装机容量,减少设备装机容量5 000kW。经过1个夏季的运行证明本优化设计可满足商场使用要求,并达到了良好的节能效果。     

Detecting and modelling nonlinearity in flexible exchange rate time series

The aim of this paper is to examine the appropriateness of nonlinear time series analysis as a framework in which to model the dynamics of exchange rates. This aim has been motivated by the questioning of the power of classical unit root tests, the accumulating amount of evidence which suggests that exchange rates follow some kind of nonlinear process, and the fact that standard asset pricing theories do not explain well the empirical observations of exchange rate movements. The paper has three major objectives. First, to test for the presence of unit roots in nominal exchange rate time series. Second, for those nominal exchange rate time series found to be stationary, to test for nonlinearity using both tests derived without a specific nonlinear alternative in mind and tests against a specific nonlinear model. Finally, we motivate the types of nonlinearity for which we test by examining a recently proposed nonlinear model of exchange rate dynamics.The authors are from the School of Finance and Economics, University of Technology, Sydney, Australia. We are extremely grateful to Alex Beliak and Alexander Khomin for their research assistance and help in developing our computer programs.