基于SPSS主成分分析法在公路客运量预测中的应用

分析选取影响公路客运量的主要因素,基于SPSS统计软件对各因素进行主成分分析,将众多相关因素简化为少数不相关因素,消除由于变量过多导致的多重共线性影响,构建了河南省公路客运量预测模型。实例证明,该模型具有较高的精度,能够满足河南省公路客运量预测的需要。     

基于模式识别的短时交通流预测

实时准确可靠的短时交通流预测是智能运输系统的基础,有很多种方法被用来对交通流进行预测.基于模式识别的交通流预测方法是较新的预测方法之一.提出一个用于短时交通流预测的模式和对应的模式识别算法,并对城区道路的交通流做了实验预测,结果表明在趋势上较为准确.     

基于四阶段法的旅游交通量预测

公路旅游交通是公路交通运输业的重要组成部分,随着现代旅游业的发展,公路旅游交通在公路交通运输业中的地位日益显现。然而目前缺乏有效的预测公路旅游交通量的方法。采用四阶段分析理论,以利川和万州地区高速公路建设为分析对象,在分析区域社会经济、旅游人数和旅游产业发展趋势的基础上,预测区域旅游交通总量,在分析基年旅游交通量分布的基础上确定各路段的交通出行量。有效地预测了利川和万州地区高速公路建设中的旅游交通量。     

1/32° real-time global ocean prediction and value-added over 1/16° resolution

A 1/32° global ocean nowcast/forecast system has been developed by the Naval Research Laboratory at the Stennis Space Center. It started running at the Naval Oceanographic Office in near real-time on 1 Nov. 2003 and has been running daily in real-time since 1 Mar. 2005. It became an operational system on 6 March 2006, replacing the existing 1/16° system which ceased operation on 12 March 2006. Both systems use the NRL Layered Ocean Model (NLOM) with assimilation of sea surface height from satellite altimeters and sea surface temperature from multi-channel satellite infrared radiometers. Real-time and archived results are available online at http://www.ocean.nrlssc.navy.mil/global_nlom. The 1/32° system has improvements over the earlier system that can be grouped into two categories: (1) better resolution and representation of dynamical processes and (2) design modifications. The design modifications are the result of accrued knowledge since the development of the earlier 1/16° system. The improved horizontal resolution of the 1/32° system has significant dynamical benefits which increase the ability of the model to accurately nowcast and skillfully forecast. At the finer resolution, current pathways and their transports become more accurate, the sea surface height (SSH) variability increases and becomes more realistic and even the global ocean circulation experiences some changes (including inter-basin exchange). These improvements make the 1/32° system a better dynamical interpolator of assimilated satellite altimeter track data, using a one-day model forecast as the first guess. The result is quantitatively more accurate nowcasts, as is illustrated by several model-data comparisons. Based on comparisons with ocean color imagery in the northwestern Arabian Sea and the Gulf of Oman, the 1/32° system has even demonstrated the ability to map small eddies, 25–75 km in diameter, with 70% reliability and a median eddy center location error of 22.5 km, a surprising and unanticipated result from assimilation of altimeter track data. For all of the eddies (50% small eddies), the reliability was 80% and the median eddy center location error was 29 km. The 1/32° system also exhibits improved forecast skill in relation to the 1/16° system. This is due to (a) a more accurate initial condition for the forecast and (b) better resolution and representation of critical dynamical processes (such as upper ocean – topographic coupling via mesoscale flow instabilities) which allow the model to more accurately evolve these features in time while running in forecast mode (forecast atmospheric forcing for the first 5 days, then gradually reverting toward climatology for the remainder of the 30-day forecast period). At 1/32° resolution, forecast SSH generally compares better with unassimilated observations and the anomaly correlation of the forecast SSH exceeds that from persistence by a larger amount than found in the 1/16° system.     

GM(1,1)模型与指数模型在基桩沉降预测中的应用

以某大型基桩的沉降预测为例,利用灰色系统理论的GM(1,1)与Aeax曲线模型进行基桩在外荷载作用下沉降量的预测。结果表明:两种模型对于呈指数变化规律的系统能获得较好的预测结果;两种模型对基桩累计沉降的预测符合工程实际,对各级荷载作用下的本级沉降预测不够合理。对两种模型关系的研究表明,两者有内在联系,都属指数曲线预测模型,且指数曲线Aeax预测模型比GM(1,1)模型应用起来更简单,方便。     

世界范围的军事变革与海军舰艇设计的新趋势

结合世界范围的军事变革与海军舰艇发展的新趋势,讨论了与舰艇设计相关的若干水动力学问题,目的在于探讨水动力学作为舰艇设计中的重要基础理论和技术之一在国防建设中的定位和作用。     

基于神经网络的地基承载力预测

对地基承载力的不确定性进行分析,将人工神经网络应用于地基承载力的确定,建立了地基承载力的神经网络模型,时勘察设计有一定的使用价值。     

微型开架式水下机器人水动力系数测定

水下机器人水动力系数的准确测定,是对机器人运动进行仿真和控制的前提。以形状复杂的开架式有缆水下机器人(ROV)作为研究对象,通过一系列水动力试验,计算出适用于开架式水下机器人模型的几个重要的实时水动力系数,为自主遥控水下机器人(ARV)的运动仿真提供了数据支撑,进而为ARV的控制奠定了基础。     

船舶水动力性能试验研究数据管理系统

本文指出了应用现代数据库技术管理船舶水动力性能试验研究数据原重要性。介绍了船研所运输部内基于客户／服务器模式的网络数据库系统，该系统用于保存、管理及开发利用运输部长期积累的船模试验研究数据。文中描述了建立数据库系统的技术，特别是开发客户端浏览、查询系统和基于船模试验数据的船舶水动力性能预报程序所用到的可视化编程技术。     

支持向量机在货运量预测中的应用研究

在分析现有货运量预测方法所存在问题的基础上,建立了货运量预测的支持向量机模型,并以我国1981～2001年的货运量和相关经济指标的历史统计数据作为学习样本,分别选用3种不同的核函数,通过拟合训练和外推预测分析,验证了支持向量机用于货运量预测的有效性,并对模型中的有关参数进行了探讨分析。