交通拥堵与温室气体排放

缓解拥堵项目可减少温室气体排放,但基于单个变量(如仅基于出行距离)的CO2排放预测并不精确.为了准确预测缓堵项目减少的CO2排放量,利用车辆运行检测技术、车辆活动数据库及根据车辆类型设计的排放模型,通过分析速度与排放的关系绘制速度-排放曲线,并结合交通运行检测数据,评价缓堵策略、速度管理策略、交通平滑策略等交通运行管理...     

基于主成分分析的城市物流发展评价

分析了城市物流的内涵,结合以往研究提出研究城市物流评价体系必须考虑它与物流辐射区经济发展的关系,深入分析了城市物流发展水平的影响因素.在此基础上,建立了科学的城市物流发展评价体系,并构建了城市物流发展水平评价的主成分分析模型.以大连、天津、上海为例进行了实证研究,验证了城市物流发展水平评价体系的有效性.     

发泡工艺参数对铝熔体泡沫生成量的影响

利用空气发泡法研究发泡温度、入射气体压力和流量以及吹气头往复运动频率对铝熔体泡沫生成量和熔体表面气泡尺寸的影响,分析了气泡尺寸对其内部气体压强和发泡工艺参数对铝熔体泡沫生成量的影响.研究结果表明,铝熔体泡沫生成量随射入空气P1V1值的增大而增加.当P1V1从5.7 MPa·cm3/min增加到7.2 MPa·cm3/min,铝熔体表面的气泡半径尺寸由6.93 mm增加到7.46 mm,铝熔体泡沫的生成率从3 210 cm3/min增加到4400 cm3/min.当入射气体P1V1为5.67 MPa·cm3/min时,发泡温度由620℃升高到640℃,气泡半径由3.57 mm增大到3.66 mm,泡沫生成量由288 g增大到2 978 cm3/min.     

多信息融合技术在船舶动力装置故障诊断中的应用

船舶动力装置工作过程中会产生大量多域故障信号,通过收集、挖掘隐藏的关联信号,可以解决船舶动力装置在故障诊断中面临的诊断时长问题.文章采用K-均值聚类算法(K-means)对数据进行聚类,聚类结果输入BP神经网络进行模型训练,并在此基础上,设计了主成分分析法(PCA)对模型进行优化.结果 显示,2种算法都能有效降低网络诊...     

发动机机油质量快速检测三法

<正>外观及气味检测法①用1个洁净的试管接取已用机油油样,用肉眼观察机油的状况。若机油比较清澈透明,仍保持着新油的颜色,表明污染不严重;油色不透明而呈雾色,表明油内进了水份;油样为灰色,表明可能被含铅汽油所污染;油样为黑色,则是燃     

高速公路路面质量指标的敏感性分析

通过建立主要成分分析模型,研究影响高速公路路面质量指标的因素。文中结合大量试验数据,对比分析了10种影响因数的敏感性。结果表明:可以用油石比、筛孔通过率、空隙率三个参数代表10个影响因素来表述其对路面性能的影响。提出的分析模型和运用的基本数学理论,可为实际中评价路面质量提供科学依据。     

基于神经网络的停车需求预测模型及应用

结合停车需求特点分析了停车需求影响因素,提出了基于主成分分析的BP神经网络停车需求预测模型,该模型主要是通过对城市中心区停车需求的经济、土地、交通的特征分析,利用主成分分析法,明确了影响停车需求的主成分,简化了神经网络的输入样本,消除了网络输入之间的相关性,提高了网络的性能,实现了公共停车需求的准确预测。     

Gas turbulence modulation model for gas-solid flows in two-fluid approach

Turbulence enhancement by particle wake effect is studied by numerical simulation of gas turbulent flows passing over particle under various particle sizes, inlet gas velocities, gas viscosity, gas density and the distance of particles. By performing dimension analysis and using the form of gas-particle interaction source term for reference, a new semi-empirical turbulence enhancement model by the particle-wake effect is proposed. The turbulence model is then incorporated into second-order moment model for simulating gas-particle flows in a horizontal channel with different wall roughness and a sudden-expansion chamber. The results show that this model is with higher calculating accuracy than another two turbulence models in comparison with the experimental results.     

主成分-聚类分析法在道路交通安全评价中的应用

利用数理统计学中的主成分-聚类分析方法对佳木斯市近几年的道路安全现状进行综合评价,结果表明,新构造的道路交通安全综合评价指标能够真实地反映道路交通安全状况,能够准确、客观地反映道路交通事故的特征、变化趋势以及事故原因类型,是对现有评价体系的补充和完善,具有广泛的实用性及推广价值。     

Study on chromatographic fingerprint of sarcandra glabra （Thunb.） by microwave-assisted extraction coupled to HPLC/DAD

Microwave-assisted extraction (MAE) was used for extraction of effective components of sarcandra glabra (Thunb.), and then chromatographic fingerprint of sarcandra glabra (Thunb.) was studied by high performance liquid chromatography/diode array detector (HPLC/DAD). The conditions of MAE were optimized by an orthogonal experiment, and then the authentication and validation of the chromatographic fingerprint were conducted. Nine peaks were identified as common peaks in the fingerprint chromatograms, and isofraxidin was considered as a reference compound and quantified. Relative standard deviations of retention time and peak area of each component were less than 3% and 8%, respectively. Similarity and difference analysis were conducted by use of PCA and relation coefficient. Twenty batches of sarcandra glabra (Thunb.) samples from two different producing areas could be classified into two different groups in the PCA model. The results showed that MAE-HPLC/DAD method was simple, efficient and stable for the study of complex chromatographic fingerprint of sarcandra glabra (Thunb.), which could provide more reliable and precise information for quality evaluation.