基于路网容量的商圈停车需求预测研究

分析商圈停车、交通拥堵与商圈持续繁荣的关系,商圈停车需求预测对商圈的可持续发展起着重要作用。为合理预见与科学估算商圈停车需求,结合路网容量、区位关系提出基于路网容量的停车需求预测模型。该模型一方面能平衡区域停车供需,缓解静态设施供需矛盾;另一方面能保证停车需求与路网容量相匹配,对动态交通起到必要的控制作用,缓解商圈周边路网的交通拥堵。最后,通过实例分析证明该模型的可行性。     

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。     

山岭隧道涌水量预测方法分类及相关因素分析

准确预测隧道涌水量能有效减少隧道病害,保护生态环境,科学指导隧道的设计与施工,而如何正确选择和应用预测方法,是准确预测的前提条件。通过广泛调研,在总结分析各类涌水量预测方法的原理和适用范围基础上,以六盘山隧道某断面为例,深入探讨了围岩渗透系数、洞室尺寸、地下水位净高变化、注浆圈厚度、注浆水平和衬砌抗渗等级等因素对隧道涌水量的影响,重点指出各类解析方法的局限性和适用条件,突出了注浆水平在实际工程中的作用,并建议山岭公路隧道衬砌抗渗等级不宜小于S8。     

基于城市轨道交通客流短时预测的运营编组设计

根据城市轨道交通客流短时预测量进行运营编组设计,更接近客流的实际运营情况,具有实时、灵活和快速响应等优点.以一周为周期,使用最近一周的历史断面客流量作为原始数据,应用嵌入式灰色神经网络组合模型进行短时预测,得到的下一周期断面客流量更符合客流不断变化的趋势.以此为基础进行运营编组设计,使其更能适应客流量的实时变化.然后将按计划运营的实际客流纳入历史客流,进行循环修正更新,作为下一周期客流短时预测基础进行运营编组设计.基于城市轨道交通客流短时预测的运营编组优化,在一定程度上可以提高城市轨道交通系统运能,提升运营效率,降低运营成本.     

瞬变电磁法对隧道含水不良地质体的探测规律

瞬变电磁法是一种对水体较为敏感的预报方法,为探索瞬变电磁法对探测隧道含水不良地质体的探测规律,通过现场大量瞬变电磁法探测实例,总结其对涌水通道、含水溶洞、含水裂隙的反应规律,以及后方低阻体对探测的干扰影响.结果表明,当探测前方存在含水通道时,视电阻率等值线会在其含水通道所在区域明显降低,且呈条带状分布,条带宽度与管道分...     

Crash prediction model for two-lane rural highways in the Ashanti region of Ghana

Crash Prediction Models (CPMs) have been used elsewhere as a useful tool by road Engineers and Planners. There is however no study on the prediction of road traffic crashes on rural highways in Ghana. The main objective of the study was to develop a prediction model for road traffic crashes occurring on the rural sections of the highways in the Ashanti Region of Ghana. The model was developed for all injury crashes occurring on selected rural highways in the Region over the three (3) year period 2005–2007. Data was collected from 76 rural highway sections and each section varied between 0.8 km and 6.7 km. Data collected for each section comprised injury crash data, traffic flow and speed data, and roadway characteristics and road geometry data. The Generalised Linear Model (GLM) with Negative Binomial (NB) error structure was used to estimate the model parameters. Two types of models, the ‘core’ model which included key exposure variables only and the ‘full’ model which included a wider range of variables were developed. The results show that traffic flow, highway segment length, junction density, terrain type and presence of a village settlement within road segments were found to be statistically significant explanatory variables (p < 0.05) for crash involvement. Adding one junction to a 1 km section of road segment was found to increase injury crashes by 32.0% and sections which had a village settlement within them were found to increase injury crashes by 60.3% compared with segments with no settlements. The model explained 61.2% of the systematic variation in the data. Road and Traffic Engineers and Planners can apply the crash prediction model as a tool in safety improvement works and in the design of safer roads. It is recommended that to improve safety, highways should be designed to by-pass village settlements and that the number of junctions on a highway should be limited to carefully designed ones.     

基于预防性养护的沥青混凝土路面使用性能预测模型研究

为了使路厩预防性养护措施选择与养护时机的确定更加合理.以沥青混凝土路面结构行为方程为基础建立了预防性养护前性能预测模型,并通过引入原路面有效厚度系数与养护措施特征系数建立了预防性养护后性能预测模型;进而简述了基于该模型的效益-费用分析法,应用该方法可以方便准确地确定最佳养护时机和养护措施.该文提出的基于预防性养护的沥青...     

热失重法在快速甄选汽油清净剂中的应用

阐述了依据清净剂及加剂汽油的热稳定性预测发动机沉积物控制的可行性.用热失重法(TGA)从8款清净剂中挑选两款特定热稳定性的清净剂,分别按规定浓度添加在汽油中对两台试验车进行1 200 km道路试验.结果表明,这两款清净剂控制CCD,IVD及PFID的实际效能与TGA预测效能基本吻合,因此认为TGA法能有效取代清净剂台架...     

基于优化灰色神经网络模型的内燃机气缸套磨损量预测的研究

气缸套磨损量是衡量汽车发动机寿命的重要因素。针对传统灰色预测模型的缺陷,采用均值修正策略,对样本数据进行预处理,实现灰色预测模型的优化;将灰色预测模型与BP网络相结合,建立了优化灰色神经网络预测模型;实例分析结果表明,优化模型能更精确地预测发动机气缸套的磨损量,为发动机的寿命预测与维修提供了更有效的方法。     

基于偏最小二乘回归的柴油机微粒排放预测

介绍了偏最小二乘回归算法的基本原理和详细算法步骤,分析了CO,HC和炭烟与微粒排放的相关性。以CO,HC和炭烟综合排放为自变量,以微粒综合排放为因变量,建立了基于偏最小二乘回归法的微粒预测模型。针对新优化匹配的参数,利用该模型对ESC循环每工况微粒排放进行预测。结果表明,模型预测结果与实测结果间差异仅为0.8%,验证了预测模型的可行性。