公路货物运输抽样调查中样本量的确定

在分析我国现行公路货物运输抽样调查方案的基础上,结合分层随机抽样中样本量的确定方法,以广东省为例,对公路货物运输抽样中的样本量进行测算,可进一步验证公路货物运输抽样调查中样本量确定的科学性,同时能为交通运输行业或其他行业类似的抽样调查提供有益的实践经验.     

The Size Effects on Process Design of Micro Deep Drawing

This paper suggested to reformulate cylindrical deep drawing parameters with dimensionless form. A diagram, in which a feasible zone is drawn to bound both the maximal allowable tension and compression stress during the deep drawing process, was established. Since it is presented in a dimensionless form, it may be applied for both conventional and micro deep drawing. Cylindrical cup deep drawing was taken as an example to show the dimensionless process design method. In addition, the size effects should be taken into account. Two kinds of size effects on micro deep drawing were investigated, which can be explained by surface layer model and strain gradient model. Numerical simulations were carried out to compare the strain distribution with or without consideration of size effect.     

质点系相对运动参考系的平衡及其平衡位置的稳定性

本文通过对Lagrange方程结构的研究得到质点系相对运动参考系的平衡方程,并在此基础上讨论了具势的平稳与半平稳系统的相对平衡位置的稳定性。     

客运班轮动态船队规划数学模型及其求解方法研究

通过对定期客运班轮运输特点分析,构建出能全面反映运量增加显著和运量增加缓慢情况下的运力更新、运力闲置、运力购置的多目标动态船队规划数学模型,模型根据绿色的定义给出了技术、经济、环保性目标函数.其数学模型具有大规模、离散和整数的特点,计算速度随着船舶数量和船型的增加以指数形式递增,造成"维数灾"难题.采用混沌初始化、维更新、非支配档案更新及基因交换对多目标离散粒子群优化算法进行改进使其适用于大规模动态船队规划,最后通过实例验证该方法的可行性并得到了相应的船队规划结论.     

基于微粒群本质特征的混沌微粒群优化算法

在总结对微粒群优化(PSO)算法本质的主要研究成果的基础上,提出了基于微粒群本质特征的混沌微粒群优化(CPSO)算法.该算法用混沌搜索方法代替随机数产生器在较好的区域搜索最优解.为了提高粒子群的多样性,用由粒子邻域内若干个个体最优位置依其适应值加权平均得到的中心位置代替标准PSO算法的全局历史最优位置.然后,根据粒子个体最优位置与上述中心位置间的距离自适应地调整混沌搜索区域半径.用几个经典测试函数的仿真结果及与其它几种PSO算法的比较结果验证了新算法的有效性.     

混凝土抗剪强度尺寸效应的细观数值模拟

混凝土的抗剪强度关系到混凝土结构的安全。采用随机骨料模型模拟混凝土的细观结构,利用有限元方法数值模拟混凝土试件的细观损伤断裂和抗剪强度,将所得数值结果与混凝土重力坝设计规范参考值比较,结果较为吻合,从而为混凝土力学性能的数值模拟开辟了新途径。同时研究表明混凝土试件的抗剪强度存在明显的尺寸效应。     

NEURAL NETWORK TRAINING WITH PARALLEL PARTICLE SWARM OPTIMIZER

Feed forward neural net works such as multi-layer perceptron,radial basis function neural net-works,have been widely applied to classification,function approxi mation and data mining.Evolu-tionary computation has been explored to train neu-ral net works as a very promising and competitive al-ternative learning method,because it has potentialto produce global mini mum in the weight space.Recently,an emerging evolutionary computationtechnique,Particle Swar m Opti mization(PSO)be-comes a hot to…     

Study of Probe Sample Size Model in Probe Vehicle Technology

In this paper, market penetration of a probe vehicle for real-time traffic data collection is discussed. A new comprehensive probe sample size model that satisfies the need of traffic flow parameter estimation and traffic network coverage is established, in which many factors like location error, probe ‘report’ transmission interval, probe data analysis interval, traffic flow density, link length, and road type are included. Based on this model, this paper proves the relationship between market penetration of the probe vehicle and other indexes, when probe data is used for link average speed estimation based on VISSIM simulation. The simulation result shows that the sample size model can provide effective probe information to accomplish the estimation of link speed.     

汽车磁粉离合器磁场的仿真研究

汽车磁粉离合器的研究与应用对于改善汽车传动系统的工作性能具有重要意义。磁场的分析与设计是磁粉离合器设计的关键,也是设计的难点所在。文章采用Matlab软件的PDE工具箱对汽车磁粉离合器的磁场进行了仿真分析,并对磁粉腔的磁场进行了求解。     

基于粒子滤波的场景事件实时识别

为解决智能监控场景中场景事件的检测与分析问题,提出了一种基于粒子滤波的场景事件实时识别方法.将场景事件分解为一系列的子事件,构成多层动态贝叶斯网络模型,模型中每一状态对应一种事件.采用Particle F ilter粒子滤波方法对模型中各节点状态的后验概率进行实时估计,以对场景事件进行实时识别.采样不同的粒子数目进行了对比仿真试验,仿真结果表明该方法能够得到较高的识别精度.