动力定位船总布置设计方法研究

文章介绍了动力定位船总布置的设计方法,通过解析归纳和分类总结法,从各组成系统和设备角度阐述了相应的总布置要求及设计要点,并根据常见的半潜平台、起重/铺管船、钻井船几种典型动力定位船舶的总布置特征,分析动力定位船,以供相近船型设计参考。     

3200t风电安装船的机电系统设计

简述了3 200 t风电安装船的总体布置及主要功能,针对柴油机驱动的全回转舵桨的动力推进装置、自动化的电站系统、风电机组DP1(动力定位)安装定位系统、风电机组的浮式运输系统和船舶座底配套高压冲洗水系统方案进行介绍与分析,从而描绘出该船在机电系统设计方面的特点与亮点。     

基于 Web 的舰船装备 IETM 系统设计与实现

装备信息化维修保障一直是相关研究机构关注的重要内容,舰船装备交互式电子技术手册（IETM ）的研究和应用对海军信息化建设和提高装备保障能力具有十分重要的意义。论文分析了 IETM 开发的关键技术,设计了基于 Web的舰船装备 IETM 系统,对推进海军维修信息化建设具有重大推进作用。     

基于本体框架的海军装备保障计划数据模型构建

为满足海军装备保障计划在保障单元间高效交流共享及自动化操作处理的要求,文章建立海军装备保障计划本体框架,对行动功能关联进行形式化表达,构建行动功能关联数据模型,形式化的阐述资源、能力以及它们之间的关联,扩展海军装备保障资源概念并构建资源数据模型。案例表达表明：行动功能关联和资源数据模型能够很好地表述装备保障行动序列、资源和能力。     

基于支持向量机回归树的内燃机振动信号趋势预测

针对标准回归树建立在统计分析基础上所存在的缺陷,提出一种基于支持向量机的回归树预测模型。首先,根据原始振动信号趋势序列构建回归树;然后,针对回归树上包含样本数过少的节点,利用支持向量机,建立能够反映重要变量与响应变量之间映射关系的回归模型。仿真结果表明:即便由于设备出现异常,导致振动信号趋势序列出现非平稳、突变情况,该方法也能准确地预测,性能优于标准分析方法,具有一定的工程实用性。     

Developing a Spatially Enabled Inventory of Recreational Boats Using Vessel Registration Data

Effective waterway management requires information on the characteristics and locations of boats. A field-based boat census—a traditional method to obtain spatially accurate information—is relatively expensive, time-consuming, and restrictive in scope. Vessel registration data, maintained by all U.S. states, is potentially a more robust information source. This research evaluated the accuracy and reliability of vessel registration data to supply location and attribute information for boats. The study premise was to use vessel registration data, which includes the mailing address of registered boat owners, to develop a spatially enabled inventory of boats. The study area comprised 12,064 salt-water accessible property parcels in two Florida counties. An on-water census (OWC) provided location and characteristics for 5,023 vessels, which were compared to 8,681 vessel registration records linked to the study area. Discrepancies between the OWC and vessel registration data were explained by a stratified, random sample of 485 telephone survey respondents. Study results show that vessel registration data accurately located and characterized roughly 81% of the boat population; in contrast, the OWC accurately located less than 56%. A conclusion is that state vessel registration data is a better alternative than an OWC for locating and characterizing boats kept along waterways.     

A new composite decision support framework for strategic and sustainable transport appraisals

This paper concerns the development of a new decision support framework for the appraisal of transport infrastructure projects. In such appraisals there will often be a need for including both conventional transport impacts as well as criteria of a more strategic and/or sustainable character. The proposed framework is based on the use of cost-benefit analysis featuring feasibility risk assessment in combination with multi-criteria decision analysis and is supported by the concept of decision conferencing. The framework is applied for a transport related case study dealing with the complex decision problem of determining the most attractive alternative for a new fixed link between Denmark and Sweden – the so-called HH-connection. Applying the framework to the case study made it possible to address the decision problem from an economic, a strategic, and a sustainable point of view simultaneously. The outcome of the case study demonstrates the decision making framework as a valuable decision support system (DSS), and it is concluded that appraisals of transport projects can be effectively supported by the use of the DSS. Finally, perspectives of the future modelling work are given.     

船坞超高型管柱支撑设计

阐述了船坞超高型管柱支撑的设计。提出了船坞区域搭载时管子支撑与外板3种连接形式下的支撑设计允许承载力的理论计算，并对目前船坞使用的φ426mm×14mm和φ500mm×18mm两种管子进行计算分析。改进了撑管的底部支撑，提高了超高型管子支撑的使用效果和安全性。     

舰船物资转运方案计算机辅助决策算法研究

瞬息万变的现代战场对大中型水面战斗舰船甲板物资转运的效率提出越来越高的要求。引入计算机辅助决策技术,在考虑多种牵制因素的情况下,快速获得最优的物资转运方案。详细分析和阐述舰船物资转运线路规划、时间计算、作业排序以及资源配班等4个主要问题的计算机解决方法,为利用计算机辅助制定最优物资转运方案提供可行途径。     

Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China

Short-term forecasting of high-speed rail (HSR) passenger flow provides daily ridership estimates that account for day-to-day demand variations in the near future (e.g., next week, next month). It is one of the most critical tasks in high-speed passenger rail planning, operational decision-making and dynamic operation adjustment. An accurate short-term HSR demand prediction provides a basis for effective rail revenue management. In this paper, a hybrid short-term demand forecasting approach is developed by combining the ensemble empirical mode decomposition (EEMD) and grey support vector machine (GSVM) models. There are three steps in this hybrid forecasting approach: (i) decompose short-term passenger flow data with noises into a number of intrinsic mode functions (IMFs) and a trend term; (ii) predict each IMF using GSVM calibrated by the particle swarm optimization (PSO); (iii) reconstruct the refined IMF components to produce the final predicted daily HSR passenger flow, where the PSO is also applied to achieve the optimal refactoring combination. This innovative hybrid approach is demonstrated with three typical origin–destination pairs along the Wuhan-Guangzhou HSR in China. Mean absolute percentage errors of the EEMD-GSVM predictions using testing sets are 6.7%, 5.1% and 6.5%, respectively, which are much lower than those of two existing forecasting approaches (support vector machine and autoregressive integrated moving average). Application results indicate that the proposed hybrid forecasting approach performs well in terms of prediction accuracy and is especially suitable for short-term HSR passenger flow forecasting.