时滞影响下受控斜拉索的参数振动稳定性

研究了轴向激励作用下受控斜拉索系统主参数共振的时滞效应,考虑了拉索垂度和几何非线性的影响,基于Hamilton变分原理建立了受控斜拉索系统轴向激励下的非线性参数振动方程,利用Galerkin方法得到时滞动力系统,运用多尺度法对受控系统的主参数共振进行了分析,得到了不同时滞值、控制增益时参数振动稳定域和受控拉索的时程曲线.研究表明,时滞影响下斜拉索振动控制系统的效果变差,参数共振的稳定域发生偏移,对受控斜拉索系统的控制效果随着时滞的增大而变差,从而对控制系统的参数设计起到指导作用.     

多层次模糊综合评价在城市交通承载力评价中的应用

城市交通承载力评价是一项复杂的系统二程.根据交通承载力的特点、评价过程及评价结果的模糊性,将城市交通承载力分为交通设施承载力和交通环境承载力,结合城市交通现状构建了交通承载力的评价指标体系.借助熵权法确定各评价指标的客观权重,并将其与模糊一致矩阵的主观赋权法相结合,提出基于组合权的多层次模糊综合评价法.评价结果表明,组合评价方法比单一评价方法更符合城市交通承载力的实际状况,从而为交通管理决策提供科学依据.     

解一元一次方程的“特事特办”

<正>解一元一次方程一般按教材归纳的去分母、去括号、移项、合并同类项、系数化为1五个步骤就行,但有些一元一次方程若按以上解法顺序来解就会使过程很复杂,如果能够根据方程的特点,灵活安排这五个步骤,即所谓"特事特办",就能化繁为简.     

变环境下相同二项型单元数据向系统数据的熵法折合

在考虑环境因子的情况下,研究给出了系统环境因子的计算方法及二项型单元数据向二项型系统数据的熵法折合公式.随后的算例表明了该方法的合理性和有效性.     

判别数项级数敛散性的一些方法和技巧

基于数项级数敛散性的判别是高等数学的一个难点,其判别方法多样,技巧性也强.结合实例分别列举了利用不等式、泰勒展开式、等价量法、对数判别法等判别数项级数敛散性的一些方法和技巧.     

基于“不动点”的数列通项的命题及其应用

以不动点为载体,与数列紧密结合求通项公式,是近年高考数学压轴题的常见题型.聂文喜[1]、林国夫[2]等均进行过初步研究,但是例证都是关于2010年之前的高考题.本文基于"不动点"的理论,给出数列通项的一些命题,并给出这些命题在2010年和2011年高考试题中的应     

反正切级数的和

基于反正切函数恒等式利用裂项法给出了一类反正切级数■的和.     

一类含有梯度项的非局部椭圆微分不等式解的Liouville型定理

本文主要研究一类具有卷积型非局部项和梯度项的拟线性椭圆微分不等式解的Liouville型定理.主要定理的证明基于非线性容度法,该方法可以处理卷积型非局部项,而且不需要使用比较原理或者极值原理.     

基于微课的高等数学教学研究

微课以其"短、小、精、趣"的特征,成为当下的热点话题.本文阐述了高等数学微课建设的特征,基于微课的高等数学教学研究的意义,基于微课的高等数学教学模式,并以"常数项级数的概念教学"为例进行剖析,探讨如何将微课作为高等数学课堂教学的有效辅助,实现高等数学教与学的最优化.     

一种多参数谱三项共轭梯度法

通过求解带有罚参数的优化问题设计共轭梯度法是一种新思路.基于Fatemi的优化问题求解,通过估计步长和选择合适的罚参数建立一个谱三项共轭梯度法,为证得算法的全局收敛性对谱参数进行修正.在标准Wolfe线搜索下证明了该谱三项共轭梯度算法的充分下降性以及全局收敛性.最后,在选取相同算例的多个算法测试结果中表明新方法数值试验性能表现良好.     

A Bayesian paired comparison approach for relative accident probability assessment with covariate information

One of the challenges managers face when trying to understand complex, technological systems (in their efforts to mitigate system risks) is the quantification of accident probability, particularly in the case of rare events. Once this risk information has been quantified, managers and decision makers can use it to develop appropriate policies, design projects, and/or allocate resources that will mitigate risk. However, rare event risk information inherently suffers from a sparseness of accident data. Therefore, expert judgment is often elicited to develop frequency data for these high-consequence rare events. When applied appropriately, expert judgment can serve as an important (and, at times, the only) source of risk information. This paper presents a Bayesian methodology for assessing relative accident probabilities and their uncertainty using paired comparison to elicit expert judgments. The approach is illustrated using expert judgment data elicited for a risk study of the largest passenger ferry system in the US.     

System reliability analysis of slope stability using generalized Subset Simulation

Slope failure mechanisms (e.g., why and where slope failure occurs) are usually unknown prior to slope stability analysis. Several possible failure scenarios (e.g., slope sliding along different slip surfaces) can be assumed, leading to a number of scenario failure events of slope stability. How to account rationally for various scenario failure events in slope stability reliability analysis and how to identify key failure events that have significant contributions to slope failure are critical questions in slope engineering. In this study, these questions are resolved by developing an efficient computer-based simulation method for slope system reliability analysis. The proposed approach decomposes a slope system failure event into a series of scenario failure events representing possible failure scenarios and calculates their occurrence probabilities by a single run of an advanced Monte Carlo simulation (MCS) method, called generalized Subset Simulation (GSS). Using GSS results, representative failure events (RFEs) that are considered relatively independent are identified from scenario failure events using probabilistic network evaluation technique. Their relative contributions are assessed quantitatively, based on which key failure events are determined. The proposed approach is illustrated using a soil slope example and a rock slope example. It is shown that the proposed approach provides proper estimates of occurrence probabilities of slope system failure event and scenario failure events by a single GSS run, which avoids repeatedly performing simulations for each failure event. Compared with direct MCS, the proposed approach significantly improves computational efficiency, particularly for failure events with small failure probabilities. Key failure events of slope stability are determined among scenario failure events in a cost-effective manner. Such information is valuable in making slope design decisions and remedial measures.     

城市举办大型体育赛会能力的评估研究

城市争办大型体育赛会的激烈竞争凸显对其举办能力评估的重要性。本文运用搜集信息、调查统计、参数估计、聚类分析的方法,构建城市举办大型体育赛会能力的评估指标体系,提出相应的评估方法和步骤。以"十冬会"为例进行实证研究,分析哈尔滨举办"十冬会"的长处与不足。评估结果与选择2010冬奥会候选城市时国际奥委会评估小组对哈尔滨的评价具有较好的一致性。本文的结论为该评估指标体系和评估方法可有效分析城市举办大型体育赛会的能力,为提高城市申办国际性大型体育赛会的竞争力提供参考。     

Effective Information for Offline Stochastic Feedback and Optimal Control of Dynamic Systems

The impact of uncertain future events on decision making in a stochastic environment is modeled in this paper. Such modeling is presented for both feedback and optimal control problems. This research overcomes the difficulties of forecasting that arise when considering future information. In this paper, we seek to find the minimum amount of information (effective information) necessary to evaluating system performance offline or to optimally control a system. The existence of effective information is proved and a methodology for determining it is developed. It is also shown that ignoring information beyond the planning horizon leads to significant performance loss and may even lead to violating the constraints of a control problem.     

Toward a situation model in a cognitive architecture

The ability to coherently represent information that is situationally relevant is vitally important to perform any complex task, especially when that task involves coordinating with team members. This paper introduces an approach to dynamically represent situation information within the ACT-R cognitive architecture in the context of a synthetic teammate project. The situation model represents the synthetic teammate’s mental model of the objects, events, actions, and relationships encountered in a complex task simulation. The situation model grounds textual information from the language analysis component into knowledge usable by the agent-environment interaction component. The situation model is a key component of the synthetic teammate as it provides the primary interface between arguably distinct cognitive processes modeled within the synthetic teammate (e.g., language processing and interactions with the task environment). This work has provided some evidence that reasoning about complex situations requires more than simple mental representations and requires mental processes involving multiple steps. Additionally, the work has revealed an initial method for reasoning across the various dimensions of situations. One purpose of the research is to demonstrate that this approach to implementing a situation model provides a robust capability to handle tasks in which an agent must construct a mental model from textual information, reason about complex relationships between objects, events, and actions in its environment, and appropriately communicate with task participants using natural language. In this paper we describe an approach for modeling situationally relevant information, provide a detailed example, discuss challenges faced, and present research plans for the situation model.     

Algebraic properties of complex fuzzy events in classical and in quantum information systems

Baer¹-semigroups are regarded as the main abstract structures for an algebraic analysis of complex fuzzy events in generalized probability theory. This assumption is verified in the case of classical probability theory in the framework of measure and integration theory. The corresponding fuzzy language is extended to the non-commutative probability theory based on operators in Hilbert space.Starting from a quantum information system a quantum probability space is constructed, which is naturally embedded in a classical information system. In this last both exact than fuzzy quantum events are represented as classical fuzzy events. Lastly, the classical fuzzy events which correspond to exact quantum events are characterized by some minimality properties.     

Bayesian Assessment of Availabilities and Unavailabilities of Multistate Monotone Systems

In the present paper we consider a multistate monotone system of multistate components. Following a Bayesian approach, the ambition is to arrive at the posterior distributions of the system availabilities and unavailabilities to the various levels in a fixed time interval based on both prior information and data on both the components and the system. We argue that a realistic approach is to start out by describing our uncertainty on the component availabilities and unavailabilities to the various levels in a fixed time interval, based on both prior information and data on the components, by the moments up till order m of their marginal distributions. From these moments analytic bounds on the corresponding moments of the system availabilities and unavailabilities to the various levels in a fixed time interval are arrived at. Applying these bounds and prior system information we may then fit prior distributions of the system availabilities and unavailabilities to the various levels in a fixed time interval. These can in turn be updated by relevant data on the system. This generalizes results given in Natvig and Eide (Scand J Statist 14:319?C327, 1987) considering a binary monotone system of binary components at a fixed point of time. Furthermore, considering a simple network system, we show that the analytic bounds can be slightly improved by straightforward simulation techniques.     

Multicriteria analysis in decision making under information uncertainty

This paper presents results of research related to multicriteria decision making under information uncertainty. The Bellman–Zadeh approach to decision making in a fuzzy environment is utilized for analyzing multicriteria optimization models (X,M models) under deterministic information. Its application conforms to the principle of guaranteed result and provides constructive lines in obtaining harmonious solutions on the basis of analyzing associated maxmin problems. This circumstance permits one to generalize the classic approach to considering the uncertainty of quantitative information (based on constructing and analyzing payoff matrices reflecting effects which can be obtained for different combinations of solution alternatives and the so-called states of nature) in monocriteria decision making to multicriteria problems. Considering that the uncertainty of information can produce considerable decision uncertainty regions, the resolving capacity of this generalization does not always permit one to obtain unique solutions. Taking this into account, a proposed general scheme of multicriteria decision making under information uncertainty also includes the construction and analysis of the so-called X,R models (which contain fuzzy preference relations as criteria of optimality) as a means for the subsequent contraction of the decision uncertainty regions. The paper results are of a universal character and are illustrated by a simple example.     

Composition and deployment of e-Health services over Wireless Sensor Networks

Providing necessary background for provisioning of a new generation of enriched services over Wireless Sensor Networks is the main effort that the scientific community is currently carrying out. These services have improved a great number of aspects related to pervasive systems such as saving resources, efficiency, reliability, scalability and low power consumption. In this paper, $\mu$SMS middleware, using an event-based service model, is presented. This novel approach makes up the design requirements previously mentioned by implementing a dynamic memory kernel and a variable payload multiplexing mechanism for the information events in order to provide advanced services. The results obtained over real-world deployments, especially those related with provision of e-Health services, reflect a significant improvement over other similar proposals, such as the RUNES approach: 50% lower memory overhead, 53% lower software components load time and 12% lower event’s propagation time.