Study on Probability Plot Correlation Coefficient of the Log-Weibull Distribution

The log-Weibull distribution is a variant of the three-parameter Weibull distribution. The probability plot of a distribution model is desired since it can help to decide on whether the model is appropriate for fitting a given dataset and can provide the initial estimate of the model parameters. The decision on the appropriateness of a distribution is somehow subjective. This paper presents a probability plot of the log-Weibull distribution(LWPP). The distribution of the probability plot correlation coefficient is studied. From this distribution, a lower confidence limit is determined for determining whether the probability plot correlation coefficient derived from a given data set is large enough. The appropriateness and usefulness of this study are illustrated by two real-world examples.     

基于附着系数曲线封闭面积的路面识别研究

以滑移率区间[0,0.16]上附着系数曲线的封闭面积作为参数指标,在Burckhardt轮胎—路面模型的基础上设计了7种典型路面的识别区间,据此在制动时完成路面识别。使用制动单轮模型进行了仿真试验,结果表明:该方法只需一次判定即可完成识别,识别快速准确,能充分利用不同路面的附着条件,提高车辆的制动效能。     

基于Kriging代理模型的高速列车悬挂参数的区间优化

针对高速列车悬挂设计参数难以选定的问题,提出一种基于Kriging代理模型的高速列车悬挂参数区间优化的方法.采用拉丁超立方试验设计方法确定仿真数据样本得到动力学仿真数据,利用偏最小二乘方法确定影响脱轨系数的主要悬挂参数,进而建立基于设计参数与仿真数据Kriging代理模型,以此模型实现悬挂参数区间优化.最后以CRH某型动车组悬挂参数为例进行了验证性优化分析,结果表明该方法正确可行.     

A bayesian dynamic linear model approach for real-time short-term freeway travel time prediction

This paper presents a Bayesian inference-based dynamic linear model (DLM) to predict online short-term travel time on a freeway stretch. The proposed method considers the predicted freeway travel time as the sum of the median of historical travel times, time-varying random variations in travel time, and a model evolution error, where the median is employed to recognize the primary travel time pattern while the variation captures unexpected supply (i.e. capacity) reduction and demand fluctuations. Bayesian forecasting is a learning process that revises sequentially the state of a priori knowledge of travel time based on newly available information. The prediction result is a posterior travel time distribution that can be employed to generate a single-value (typically but not necessarily the mean) travel time as well as a confidence interval representing the uncertainty of travel time prediction. To better track travel time fluctuations during non-recurrent congestion due to unforeseen events (e.g., incidents, accidents, or bad weather), the DLM is integrated into an adaptive control framework that can automatically learn and adjust the system evolution noise level. The experiment results based on the real loop detector data of an I-66 segment in Northern Virginia suggest that the proposed method is able to provide accurate and reliable travel time prediction under both recurrent and non-recurrent traffic conditions.     

对空情报雷达探测威力试验飞行设计

在分析雷达威力探测试验条件和方法的基础上,对威力试验的航线及飞行架次进行了设计,研究了发现概率区间与飞行试验的观测次数关系及误差分析,以及发现概率区间与发现概率曲线关系;仿真实验表明,在距离区间内选择合适的观测次数和发现概率,对对空情报雷达威力试验有着直接影响。     

极坐标系下的航迹灰色区间关联算法

研究了雷达组网中时变系统偏差存在时的航迹关联问题。在分析时变偏差影响的基础上,从航迹的不确定区域着手,提出一种基于极坐标测量参数的航迹灰区域表示方法,并以此建立了区间灰数关联模型,实现了无需对系统误差配准的航迹关联配对。仿真结果表明,算法是有效的,并且具有较好的抗差性能。     

车用电控柴油机润滑油更换里程研究

详细地介绍了车用电控柴油机润滑油更换里程的研究过程。研究结果表明:4.5 L和6.7 L车用电控柴油机使用推荐的CH4-15W/40润滑油时,在常用典型工作循环(城市工况、高速工况、国道工况)下,润滑油更换里程可以延长到20 000公里。     

How to assess sustainability of suppliers in volume discount context? A new data envelopment analysis approach

In this paper, we reformulate conventional data envelopment analysis (DEA) models and propose a novel method for evaluating sustainability of suppliers in the presence of interval volume discount offers, fuzzy data, and ordinal data. To this end, we convert all data into interval data. To convert fuzzy data into interval data, we use nearest weighted interval approximation by applying weighting function and we convert each ordinal data into interval one. Then, using enhanced Russell model, interval efficiencies are obtained. After that, using preference degree approach, we rank suppliers. Finally, a case study is presented to illustrate our proposed approach.     

复杂周期信号的等间隔序列分选

分析各种周期信号在直方图上的规律,提出一种等间隔序列方法来分选复杂周期信号,利用等间隔序列比原序列含有更丰富的周期信息,减小了直方图方法在复杂信号环境中判别信号周期的级数和复杂性,从而提高了分选"周期性信号"的速度.     

变时窗滤波技术压缩瞬变电磁测深数据

研究目的:对采样密度高、数据量大的等间隔瞬变电磁测深数据进行反演解释时,必须对数据进行无损滤波和压缩,得到反映信号衰减规律的不等间隔类对数采样瞬变电磁测深数据.本文特对此进行研究.研究结论:在瞬变测深晚期,尽管数据信噪比非常低,利用变时窗滤波技术仍然可以获得符合规律的瞬变衰减曲线.因此,变时间(时窗)依赖滤波方法是对密度非常大的等间隔瞬变电磁测深数据进行无损压缩的良好工具.