铁路线路单元质量管理信息系统框架探讨

铁路行业的高速发展向铁路线路管理提出了更高要求,亟需信息系统辅助管理。通过研究分析国内外铁路线路信息管理系统现状,明确线路单元优化划分和养护维修计划优化制定是系统的发展方向。依据公路单元划分的方法,探讨铁路轨道单元划分的原则和方式,研究"秩和检验法"划分线路单元的具体步骤,总结轨道单元划分管理的实际应用效果。参考国外铁路线路信息管理系统的框架搭建形式,结合单元管理思想探讨系统各模块功能,搭建线路检测、单元划分、计划制定、实施效果反馈的连续性管理框架,并在计划管理模块中采用案例推理技术(CBR),设计两次推理过程,建立检测数据与对策源案例的联系,优化养护维修计划制定方法,为铁路线路的管理提供决策支持。     

基于CBR的无线闭塞中心故障诊断方法研究

无线闭塞中心(RBC)系统结构、功能复杂,维护过程中积累了大量的现场诊断案例。为了有效利用历史诊断经验,将人工智能CBR(Case-Based Reasoning)技术引入到无线闭塞中心的故障诊断中,分析基于CBR的RBC故障诊断流程,运用面向对象的方法对RBC故障案例进行了表示,提出基于R-S(Rough Set)理论的案例特征属性权重计算方法,采用融合最近邻和余弦函数的相似度算法改进了传统案例推理技术的相似度算法。最后以RBC维护终端的具体案例验证提出方法的有效性。     

Ontologies for transportation research: A survey

Transportation research relies heavily on a variety of data. From sensors to surveys, data supports day-to-day operations as well as long-term planning and decision-making. The challenges that arise due to the volume and variety of data that are found in transportation research can be effectively addressed by ontologies. This opportunity has already been recognized – there are a number of existing transportation ontologies, however the relationship between them is unclear. The goal of this work is to provide an overview of the opportunities for ontologies in transportation research and operation, and to present a survey of existing transportation ontologies to serve two purposes: (1) to provide a resource for the transportation research community to aid in understanding (and potentially selecting between) existing transportation ontologies; and (2) to identify future work for the development of transportation ontologies, by identifying areas that may be lacking.     

知识规则的可信度在游艇产品配置系统中的应用研究

游艇客户在选择配置产品时通常会提出各种个性化需求,因此在构建游艇产品配置系统时,需要对配置结果进行评价,作为客户满意产品的选择依据。在建立客户需求知识库的基础上,结合运用加权法与规则可信度方法,提出了基于加权的产生式规则可信度推理方法,并应用到客户满意度的推理机中,最后通过实例验证在游艇产品配置系统中对客户选择方案集做出最终满意度评估。     

Assessment of factors associated with travel time reliability and prediction: an empirical analysis using probabilistic reasoning approach

Significant efforts have been made in modeling a travel time distribution and establishing measures of travel time reliability (TTR). However, the literature on evaluating the factors affecting TTR is not well established. Accordingly, this paper presents an empirical analysis to determine potential factors that are associated with TTR. This study mainly applies the Bayesian Networks model to assess the probabilistic association between road geometry, traffic data, and TTR. The results from this model reveal that land use characteristics, intersection factors, and posted speed limits are directly associated with TTR. Evaluating the strength of the association between TTR and the directly related variables, the log odds ratio analysis indicates that the land use factor has the highest impact (0.83) followed by the intersection factor (0.57). The findings from this study can provide valuable resources to planners and traffic operators in their decision-making to improve TTR with quantitative evidence.     

人工智能在舰船避碰领域的应用

讨论人工智能技术的分类,分析模糊逻辑、神经网络(模糊神经网络)、专家系统、主体(A-gent)和基于案例推理(CBR)技术等各种人工智能技术在避碰领域的研究现状,展望了人工智能技术在避碰领域的发展前景.     

基于案例推理和神经网络的车辆故障诊断研究

将人工神经网络和基于案例的推理技术相结合,应用于车辆故障诊断系统中,建立了应急故障诊断模型;基于此模型,研究了车辆维修案例的表示方法并设计了CB神经网络的学习规则,通过系统的仿真训练和仿真诊断,该模型有效地提高了故障诊断的效能,满足车辆应急故障诊断的需求。     

A risk assessment model with systematical uncertainty treatment for container shipping operations

ABSTRACT

The substantial adverse effects of risk factors on container shipping and logistics promoted a deep integration of risk analysis into the decision-making process. This paper aims to develop a well-grounded quantitative model to operational risk in a container shipping context. Considering uncertainty as a primary component of the risk concept, methods were employed in an inter-complementary manner to enable not only a sense of foreseeability but also a deeper look into the weaknesses of the knowledge base. The intersubjectivity of the input extraction process was supported by the Evidential Reasoning (ER) algorithm. Risks are then assessed based on a Fuzzy Rules Bayesian Network (FRBN) model with a 2-level parameter structure before meaningful interpretations can be derived through a new risk mapping approach. Besides an illustrative case study, the model was tested by sensitivity analysis and an examination of multiple validity claims.     

基于模糊相似优先比的强夯有效加固深度范例推理研究

运用模糊相似优先比的概念,构造了一个强夯有效加固深度预测的模型。对每一个影响强夯有效加固深度的因素,分别建立了目标范例与源范例之间的模糊相似优先关系。经过影响因素之间的两两比较,获得不同的影响因素下强夯地基的目标范例与源范例之间的相似性序列,计算得到强夯地基有效加固深度目标范例和源范例之间的综合相似性序列,从而找到与强夯有效加固深度目标范例最相似的源范例,实现了有效加固深度的预测。实例评价结果与实际有效加固深度结果一致。     

智能冲模CAD系统中的CBD方法研究

介绍了实例推理方法（CBR）的一般原理，通过对比冲模设计过程和CBR方法，说明了基于实例的设计（CBD）方法用于智能冲模CAD系统的合理性，并研究了其中的关键技术。