基于路网二次分层模型的出行路径诱导优化方法

为了提高出行诱导路径搜索的效率和优度,提出了一种基于道路功能以及交通状态划分的路网二次分层模型,模型从道路的功能角度进行路网的初分层,从道路交通状态角度,通过设定的交通状态阂值进行路网的次分层,建立的路网二次分层模型从宏观方面反映路网的结构,从微观方面反映路网运行的交通参数;利用路网二次分层模型所划分的各层路网之间的协同,借助限制区域的A‘算法进行最优路径的“三段巡径”过程。实例表明该算法实用、高效,有助于搜索得到最优出行路径。     

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匝道控制是缓解快速路拥堵的有效措施,而且有增加通行流量、提高运行效率、减少交通事故的功能,随着国民经济的提高,社会公众对环境污染的关注越来越高,所以研究考虑尾气排放减少的匝道控制是立足民生的课题.本文算法考虑了尾气排放因素,同时兼顾两个目标,一是减少总车辆旅行时间,二是最大量地减少尾气排放.利用Paramics仿真软件对算法进行了模拟实验,并且运用CMEM交通排放模型进行了计算,分析结果显示新算法有效地降低了总车辆旅行时间,而且比ALINEA算法更能降低匝道路段的尾气排放量和排队数,特别是在上坡坡度较大的情况下,新算法可以更多的减少尾气排放总量.     

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无线传感网是采集实时交通信息的重要工具.因其节点能量有限,必须设计高能效的分簇路由算法以延长网络周期.本文通过建立一种智能交通中无线传感器网络的应用模型,根据其特点和要求分析LEACH协议的优缺点并提出一种能量负载均衡的分簇算法.该算法对LEACH协议当中的簇首机制进行改进,综合考虑候选节点的剩余能量和簇首节点的分布位置;建立簇间多跳路由机制以避免单跳通信的大能量消耗;创造一种簇重构方法,避免过于频繁的簇重构引起的不必要能量消耗.仿真结果表明,能量均衡算法可有效平衡节点能量消耗分布,延长网络生命周期,可很好的应用于基于WSN的ITS当中.     

无线射频识别技术在高速公路二义性路径标识系统中的应用

论述了无线射频识别技术在二义性路径标识系统中的必要性及意义,通过数学建模并仿真分析,介绍了基础防碰撞算法及其改进算法,对标签快速、准确识别具有一定的参考意义。     

Multi-objective bilevel construction material transportation scheduling in large-scale construction projects under a fuzzy random environment

Abstract

This paper investigates a transportation scheduling problem in large-scale construction projects under a fuzzy random environment. The problem is formulated as a fuzzy, random multi-objective bilevel optimization model where the construction company decides the transportation quantities from every source to every destination according to the criterion of minimizing total transportation cost and transportation time on the upper level, while the transportation agencies choose their transportation routes such that the total travel cost is minimized on the lower level. Specifically, we model both travel time and travel cost as triangular fuzzy random variables. Then the multi-objective bilevel adaptive particle swarm optimization algorithm is proposed to solve the model. Finally, a case study of transportation scheduling for the Shuibuya Hydropower Project in China is used as a real world example to demonstrate the practicality and efficiency of the optimization model and algorithm.     

Disruption Management of an Inequality-Based Multi-Fleet Airline Schedule by a Multi-Objective Genetic Algorithm

Abstract

This paper presents a novel application of a Method of Inequality-based Multi-objective Genetic Algorithm (MMGA) to generate an efficient time-effective multi-fleet aircraft routing algorithm in response to the schedule disruption of short-haul flights. It attempts to optimize objective functions involving ground turn-around times, flight connections, flight swaps, total flight delay time and a 30-minute maximum delay time of original schedules. The MMGA approach, which combines a traditional Genetic Algorithm (GA) with a multi-objective optimization method, can address multiple objectives at the same time, then explore the optimal solution. The airline schedule disruption management problem is traditionally solved by Operations Research (OR) techniques that always require a precise mathematical model. However, airline operations involve too many factors that must be considered dynamically, making a precise mathematical model difficult to define. Experimental results based on a real airline flight schedule demonstrate that the proposed method, Multi-objective Optimization Airline Disruption Management by GA, can recover the perturbation efficiently within a very short time. Our results further demonstrate that the application can yield high quality solutions quickly and, consequently, has potential to be employed as a real-time decision support tool for practical complex airline operations.     

一种永磁同步电机声品质主观评价方法研究

对永磁同步电机的稳态信号声品质进行了分析,并以声压级、响度、尖锐度、语音清晰度、波动度、粗糙度和音调度作为评价指标,建立了永磁同步电机声品质评价体系.采用分组成对比较法进行了主观评价,通过Bradley-Terry算法对评价结果进行了优化处理,分别搭建多元线性回归预测模型和MPGA-RBF预测模型,通过预留的检验样本对...     

基于LMS和SDP的发动机异响诊断方法研究

为有效提取发动机声信号特征,以诊断发动机的异响,提出了一种以最小均方算法和对称点图形算法相结合的发动机异响诊断方法。采用最小均方算法去除信号中的噪声,还原发动机声信号,而利用SDP图形技术将信号转换为极坐标图形,得以判断发动机是否产生异响。通过仿真与试验,验证了该方法的有效性。     

四回路保护阀的结构及其工作过程分析

分析了四回路保护阀的结构及工作过程,重点阐述了典型保护阀的功能、特点及在整车上的应用。     

路面裂缝图像自动识别算法综述

路面裂缝自动检测对于路面养护管理、路面性能评价与预测、路面材料和结构设计具有重要的实用价值,但快速、准确、全面且稳定地识别路面裂缝一直是个难题.为此,对路面裂缝自动检测研究现状进行综述,包括以图像增强和去噪为目的的预处理方法,基于阈值分割、边缘检测和种子生长的空间域识别算法,以小波变换为代表的频域识别算法,基于有监督学习的识别算法及其他裂缝识别方法;指出既有裂缝识别算法存在易受光照和油污等因素的影响、裂缝识别图像连续性差和识别速度和精度较低等不足.最后,提出综合考虑边界和区域特征消除纹理和噪声干扰、基于局部和全局信息设计优化识别算法和基于三维图像进行裂缝识别等研究展望,为裂缝自动识别算法的改进提供参考.