一类有竞争的物流配送中心选址模型

对已有多个配送中心存在的前提出，新增配送中心为获取最大市场占有量如何进行有效的选址决策问题进行了研究，建立了一个选址决策模型，把求解的问题归结为无约束的非线性规划问题，并给出了迭代算法，最后对如何解决考虑多种选址影响因素及多个新增配送中心的复杂情况进行了讨论。     

Integrated optimization of location and signal timings for midblock pedestrian crosswalk

Finding the optimal location and signal timing plan is one of the most critical operational issues for a signalized midblock crosswalk on an arterial section, which is increasingly being installed in highly populated areas in developing countries such as China. This paper presents a multiobjective optimization model and an efficient solution algorithm for a one‐ or two‐stage midblock crosswalk on an arterial section. The proposed model aims to produce the optimal location and corresponding signal settings to balance the trade‐off between pedestrian delays and vehicular bandwidth when the signals of the crosswalk and adjacent intersections are coordinated. The proposed model has three distinguishing features: (i) the costs for both pedestrians and vehicles are considered in a unified framework; (ii) the location and signal settings of the midblock crosswalk are simultaneously optimized; and (iii) a multiobjective optimization approach is developed to study the effectiveness of the midblock crosswalk under conditions in which the priorities between pedestrian and vehicle flows differ. A nondominated sorting genetic algorithm II (NSGA II)‐based algorithm is developed to solve the model efficiently. The results of the case study showed that the proposed model would help traffic practitioners, researchers, and authorities properly locate and signalize a one‐ or two‐stage midblock pedestrian crosswalk on an arterial section. Copyright © 2015 John Wiley & Sons, Ltd.     

A Comparative Study of Three Multivariate Short-Term Freeway Traffic Flow Forecasting Methods With Missing Data

Short-term traffic flow forecasting is a critical function in advanced traffic management systems (ATMS) and advanced traveler information systems (ATIS). Accurate forecasting results are useful to indicate future traffic conditions and assist traffic managers in seeking solutions to congestion problems on urban freeways and surface streets. There is new research interest in short-term traffic flow forecasting due to recent developments in intelligent transportation systems (ITS) technologies. Previous research involves technologies in multiple areas, and a significant number of forecasting methods exist in the literature. However, most studies used univariate forecasting methods, and they have limited forecasting abilities when part of the data is missing or erroneous. While the historical average (HA) method is often applied to deal with this issue, the forecasting accuracy cannot be guaranteed. This article makes use of the spatial relationship of traffic flow at nearby locations and builds up two multivariate forecasting approaches: the vector autoregression (VAR) and the general regression neural network (GRNN) based forecasting models. Traffic data collected from U.S. Highway 290 in Houston, TX, were used to test the model performance. Comparison of performances of the three models (HA, VAR, and GRNN) in different missing ratios and forecasting time intervals indicates that the accuracy of the VAR model is more sensitive to the missing ratio, while on average the GRNN model gives more robust and accurate forecasting with missing data, particularly when the missing data ratio is high.     

船舶航向自适应神经网络鲁棒跟踪控制

针对存在不确定性和带有完全未知时变环境扰动的船舶航向非线性控制系统,将指令滤波技术和反步法相结合,设计了一种船舶航向自适应神经网络鲁棒跟踪控制器,该控制器的提出不依赖于外部扰动任何的先验信息。首先,利用神经网络补偿船舶航向非线性控制系统中的非线性项;设计自适应律在线更新神经网络权重向量和估计时变环境扰动的未知界。为了避免传统反步法中对虚拟控制律的反复求导,引入指令滤波技术,使得所设计的航向自适应神经网络跟踪控制器具有结构简单、易于工程实现的特点。理论分析表明,所设计的控制器能使船舶实际输出航向以任意期望的精度跟踪给定的参考航向,保证船舶航向闭环控制系统中所有信号一致最终有界。最后,以大连海事大学远洋实习船“育龙”轮为例进行仿真,仿真结果验证了所提控制器的有效性和鲁棒性。     

基于斜拉索张力测定的斜拉桥健康诊断

应用试验校正的高精度三维有限元模型,对斜拉桥主梁结构损伤位置识别的斜拉索张力指标进行了研究。模拟12种可能的损伤情况,研究了基于斜拉索局部模态基频构造索张力指标的方法,索张力指标对各损伤情况下损伤位置的识别效果和对损伤程度的敏感性。结果表明,用斜拉索局部模态基频所构造的张力指标对不同的损伤程度呈现较好的稳定性和灵敏性,对模拟的12种损伤情况的正确识别率可达75%。该方法的突出优点是只需测量斜拉索局部振动模态的基频,就能获得较好的损伤识别效果,比其他面向损伤检测的测量容易得多。该方法可十分方便地推广应用于悬索桥加劲梁结构的损伤定位,具有较高的实用价值。     

贝叶斯网络在电控发动机燃油系统故障分析中的应用

贝叶斯网络(Bayesian Network)是近年来发展起来的一种基于概率理论的推理工具,本研究简要介绍了贝叶斯网络的基本理论,建立了电控发动机燃油供给系统故障信息的贝叶斯诊断网络,并利用Hugin Expert软件计算当燃油供给系统某一部件出现故障时不同故障现象出现的概率。研究表明,贝叶斯诊断网络能够有效诊断电控发动机燃油供给系统故障信息关联度。     

地铁数字电流保护技术的应用

针对现行地铁供电系统保护方案在应用过程中暴露出的一些不足,提出一种以智能变电站GOOSE网络通信技术为基础的数字电流保护方法,并详细介绍其动作逻辑、组网方案、硬件系统设计及应用情况.通过比较发现,相对于其他地铁网络保护方法,数字电流保护方法通过合理运用IEC61850技术和最新软硬件技术,在可靠性和稳定性方面得到很大提升.利用Smartbits测试仪和RTDS仿真系统,对数字电流保护方法进行试验验证.该保护方法已经在南京地铁的部分线路中投入运行,并在多次故障中正确动作.     

PDM在客车制造企业的应用规划

PDM（产品数据管理）技术在制造业中的应用正在迅速普及。本文结合为武汉客车厂开发PDM的实际经验。阐述客车制造企业开发PDM的规划。     

网络时代学生心理健康教育工作探析

网络的快速、方便给世界增添了不少亮色,为人类的发展做出巨大贡献,但也引发了许多问题：黄色网站和虚假信息、黑客入侵、病毒传播、网络攻击、信息窃取、网络犯罪等给学生心理也带来了极大的冲击.研究网络时代学生心理问题,探索新形势下学生心理健康教育工作的新思路、新方法、新手段,是摆在广大教育工作者面前的一个崭新课题.     

树脂混凝土强度预测的神经网络模型

本文运用均匀设计的方法进行树脂混凝土的配合比设计,用较少的试验取得较好的效果;建立了树脂混凝土的强度预测的神经网络模型,对试验的数据进行了训练和仿真,预测的结果与试验结果吻合非常好。