基于SysML的三余度飞控计算机系统建模方法研究

提出了一种基于Sys ML的三余度飞控计算机设计方法.在设计过程中,利用Sys ML静态图构建三余度飞控计算机系统结构模型;利用Sys ML的动态行为图构建余度管理算法模型,实现了三余度飞控计算机系统模型.以某三余度飞控计算机系统为例,构建三余度飞控计算机系统结构模型;设计计算机同步算法、监控表决算法并对算法进行建模.最后,通过所构建的仿真环境进行验证,结果表明所提出方法可行有效.     

基于WRT方法的港口危化品物流风险评估研究

针对港口危化品物流风险管理中风险因素众多和交互影响的复杂性,构建港口危化品物流的WRT风险评估模型.首先基于物理-事理-人理WSR理论构建港口危化品物流风险评估指标框架,其次通过风险过滤和排序RFRM理论对风险因素进行双重过滤,保留关键风险因素.然后基于TSS情景构建理论从物理、事理和人理三个层面构建港口危化品物流的多维风险情景,通过深入剖析各风险情景下风险因素之间的耦合关系,刻画港口危化品物流中的不同风险状态与风险源最后,基于熵权法和贝叶斯理论对我国7个重要港口进行多维情景风险评估,结果表明天津港和南京港整体风险较大,多数情况下二维情景风险大于三维情景风险,同时从多维风险情景下对物理、事理、人理的耦合风险进行分析,展示了各港口的薄弱环节,最后为港口危化品物流风险管理提出建议.     

基于关键链和混合优化算法的舰船多项目并行建造进度管理方法

针对舰船多资源约束、多项目并行建造条件下进度优化与管理能力的不足,提出了一套进度管理方法。首先,基于关键链理论给出了多资源约束下舰船多项目并行建造进度管理步骤。其次,构建了舰船多项目并行建造进度优化模型,可实现在优化并行项目总工期的过程中通过合理分配各种资源获取最佳项目实施组合。最后,设计了适合于舰船建造等大型复杂工程项目求解的混合优化算法,并通过算例验证了方法的实用性。     

下一代密集WLAN网络干扰管理机制

在密集高效无线局域网部署场景中,针对传统802.11协议造成用户公平性差和吞吐量低的问题,提出一种以用户为中心的资源配置方法。该方法通过对用户进行识别分类,以用户为中心配置信道和功率,在保证用户公平性的前提下,最大化网络吞吐量。提出的功率控制机制和用户识别方法可以很简单的应用于现有无线局域网系统中。仿真结果表明,提出的资源配置方法平均提升单位基本服务集吞吐量47.3%,干扰最严重的基本服务集的吞吐量提升190%,每个基本服务集的边缘用户的吞吐量平均提升约74.3%。     

Short-run wavelet-based covariance regimes for applied portfolio management

Decisions on ass et allocations are often determined by covariance estimates from historical market data. In this paper, we introduce a wavelet-based portfolio algorithm, distinguishing between newly embedded news and long-run information that has already been fully absorbed by the market. Exploiting the wavelet decomposition into short- and long-run covariance regimes, we introduce an approach to focus on particular covariance components. Using generated data, we demonstrate that short-run covariance regimes comprise the relevant information for periodical portfolio management. In an empirical application to US stocks and other international markets for weekly, monthly, quarterly, and yearly holding periods (and rebalancing), we present evidence that the application of wavelet-based covariance estimates from short-run information outperforms portfolio allocations that are based on covariance estimates from historical data.     

Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods

Financial distress prediction (FDP) has been widely considered as a promising approach to reducing financial losses. While financial information comprises the traditional factors involved in FDP, nonfinancial factors have also been examined in recent studies. In light of this, the purpose of this study is to explore the integrated factors and multiple models that can improve the predictive performance of FDP models. This study proposes an FDP framework to reveal the financial distress features of listed Chinese companies, incorporating financial, management, and textual factors, and evaluating the prediction performance of multiple models in different time spans. To develop this framework, this study employs the wrapper-based feature selection method to extract valuable features, and then constructs multiple single classifiers, ensemble classifiers, and deep learning models in order to predict financial distress. The experiment results indicate that management and textual factors can supplement traditional financial factors in FDP, especially textual ones. This study also discovers that integrated factors collected 4 years prior to the predicted benchmark year enable a more accurate prediction, and the ensemble classifiers and deep learning models developed can achieve satisfactory FDP performance. This study makes a novel contribution as it expands the predictive factors of financial distress and provides new findings that can have important implications for providing early warning signals of financial risk.     

On the Difficulty of Measuring Forecasting Skill in Financial Markets

The use of correlation between forecasts and actual returns is commonplace in the literature, often used as a measurement of investors' skill. A prominent application of this is the concept of the information coefficient (IC). Not only can the IC be used as a tool to rate analysts and fund managers but it also represents an important parameter in the asset allocation and portfolio construction process. Nevertheless, a theoretical understanding of it has typically been limited to the partial equilibrium context where the investing activities of each agent have no effect on other market participants. In this paper we show that this can be an undesirable oversimplification and we demonstrate plausible circumstances in which conventional empirical measurements of IC can be highly misleading. We suggest that improved understanding of IC in a general equilibrium setting can lead to refined portfolio decision making ex ante and more informative analysis of performance ex post. Copyright © 2015 John Wiley & Sons, Ltd.     

公共文化服务体系下的高校图书馆编目业务社会化管理

分析了图书馆编目业务实行社会化管理后存在的问题，从图书馆领导层、书商领导层、图书馆编目员、书商编目员等角度，探讨了如何在实行社会化管理后保证编目数据的质量，以促进编目社会化管理的顺利进行。     

一站式高校图书馆纸质期刊的采购模式与细致管理

针对一站式高校图书馆的格局特点，阐述了一站式高校图书馆采购模式的更新，探讨了纸质期刊在日常管理中存在的问题，提出了一站式高校图书馆纸质期刊管理对策。     

关于高校图书馆书库管理的思考

书库是一个图书馆的中心，高质量的书库管理工作直接决定了整个图书馆的服务质量。针对图书馆书库管理中存在的问题，提出了提高书库管理工作质量的措施，使书库能更高效地为读者服务。