宁夏地区沥青路面养护专家系统的开发

传统的项目层次的沥青路面养护决策方法是依靠养护工程师在现场进行评价决策,这种传统的决策方法虽然准确有效,但也存在效率低、决策有差异性、区域性养护标准不统一等问题。本研究通过对宁夏地区普通公路养护专家知识和经验的提取,建立了一套基于路面管理系统(CPMS)数据库和专家知识的沥青路面养护专家系统,它能够解决基层公路管理部门所面临的养护决策问题,是对CPMS网级系统的补充和对CPMS技术的完善。     

两级模糊优选模型及非结构性模糊决策理论在桥梁方案比选中的应用

选择桥梁设计方案,涉及诸多因素,这些因素在某些情况下相容,在某些情况下又相斥。为了协调这些复杂关系,并降低人为因素的影响,本文引入两级模糊优选模型及非结构性模糊决策理论。并运用此模型,进行一桥梁的设计选型优化,得到了比较理想的结果,证明了此模型在桥梁方案比选中的实用性。     

基于LMS自适应滤波的模糊控制主动悬架研究

以车辆操纵稳定性及行驶平顺性为控制目标，根据路面一车辆系统的特点，提出一种在线可调整的模糊控制算法，利用LMS自适应模块调整模糊控制器的自调整因子，改善单一模糊控制算法对专家先期经验的依赖。针对简化的车辆模型，以路面信号作为激励源，进行悬架系统的振动控制研究，结果表明提出的算法对车辆悬架系统的振动控制具有较好的适应性。     

模糊自整定PID参数控制器及其在汽车测试设备中的应用

在汽车的控制及测试设备中，广泛使用常规的ＰＩＤ控制器，由于它不具备在线整定ＰＩＤ参数的功能，因此在参数时变较大的系统，其性能难以满足要求。为此本文应用模糊控制技术实现了ＰＩＤ控制器的参数在线自整定，获得了比较理想的效果。本文以汽车传动轴试验台为例，详细地阐述了模糊控制器的设计原理及计算机软件设计方法。     

关于一、三级公路安全性认知因素的试验建模研究

在实测86处一级公路典型路段和188处三级公路典型路段道路结构基础上,确定驾驶员对国道一、三级公路的安全性认知因素集,进而针对一级公路的38处样本路段和三级公路的77处样本路段,组织47名驾驶人员进行现场认知评价试验,并应用模糊集合原理和模糊统计方法对评价试验得到的2829组(一级路673组、三级路2156组)有效认知试验评语数据进行分析处理,得到一、三级公路安全性认知因素的模糊评价隶属函数,从而给出驾驶人员对一、三级公路道路条件和交通环境的安全性模糊评价模型。     

基于FWD检测结果旧路地基脱空状况的模糊评定

总结了利用FWD检测旧路基层脱空的方法,分析其各自的优缺点。在此基础上优化评价方法,引入模糊思想,提出一种新的地基脱空评价方法—模糊评定法,详细介绍模糊评定模型的建立方法和过程,并结合G325国道粤境开平段路面大修改善工程,探讨利用FWD检测结果现场模糊评定旧混凝土路面地基的脱空状态。工程实践表明,该方法取得了很好的实用效果,有效地指导了路面大修施工。     

Fuzzy-logic applied to yaw moment control for vehicle stability

In this paper, we propose a new yaw moment control based on fuzzy logic to improve vehicle handling and stability. The advantages of fuzzy methods are their simplicity and their good performance in controlling non-linear systems. The developed controller generates the suitable yaw moment which is obtained from the difference of the brake forces between the front wheels so that the vehicle follows the target values of the yaw rate and the sideslip angle. The simulation results show the effectiveness of the proposed control method when the vehicle is subjected to different cornering steering manoeuvres such as change line and J-turn under different driving conditions (dry road and snow-covered).     

基于模糊层次的铁路混装货物装运安全评价研究

随着客户运输需求的多样化升级,采用铁路混装货物装运模式在提升铁路运输效率、吸引多样货源等方面相较于单一品名装运显示出一定的优越性,同时混装货物装运面临的安全压力相较于单一品名装运出现骤增。为保障铁路混装货物装运安全,在阐述混装货物装运特点及安全控制要点的基础上,从"人防""物防""技防"3方面构建混装货物装运安全评价指标体系,采用层次分析法确定各指标权重,并利用模糊综合评价法对铁路混装货物装运安全进行评价,通过实例验证该评价方法的实用性及有效性,为铁路混装货物装运安全评价提供依据。     

A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study

The management of products’ end-of-life and the recovery of used products has gained significant importance in recent years. In this paper, we address the carbon footprint-based problem that arises in a closed-loop supply chain where returned products are collected from customers. These returned products can either be disposed of or be remanufactured to be resold as new ones. Given this environment, an optimization model for a closed-loop supply chain (CLSC) in which carbon emission is expressed in terms of environmental constraints, i.e., carbon emission constraints, is developed. These constraints aim to limit the carbon emission per unit of product supplied with different transportation modes. Here, we design a closed-loop network where capacity limits, single-item management and uncertainty on product demands and returns are considered. First, fuzzy mathematical programming is introduced for uncertain modeling. Then, the statistical approach to the possibility to synthesize fuzzy information is utilized. Therefore, using a defined possibilistic mean and variance, we transform the proposed fuzzy mathematical model into a crisp form to facilitate efficient computation and analysis. Finally, the risk caused by violating the estimated resource constraints is analyzed so that decision makers (DMs) can trade off between the expected cost savings and the expected risk. We utilize data from a company located in Iran.     

Balancing energy consumption and risk of delay in high speed trains: A three-objective real-time eco-driving algorithm with fuzzy parameters

Eco-driving is an energy efficient traffic operation measure that may lead to important energy savings in high speed railway lines. When a delay arises in real time, it is necessary to recalculate an optimal driving that must be energy efficient and computationally efficient.In addition, it is important that the algorithm includes the existing uncertainty associated with the manual execution of the driving parameters and with the possible future traffic disturbances that could lead to new delays.This paper proposes a new algorithm to be executed in real time, which models the uncertainty in manual driving by means of fuzzy numbers. It is a multi-objective optimization algorithm that includes the classical objectives in literature, running time and energy consumption, and as well a newly defined objective, the risk of delay in arrival. The risk of delay in arrival measure is based on the evolution of the time margin of the train up to destination.The proposed approach is a dynamic algorithm designed to improve the computational time. The optimal Pareto front is continuously tracked during the train travel, and a new set of driving commands is selected and presented to the driver when a delay is detected.The algorithm evaluates the 3 objectives of each solution using a detailed simulator of high speed trains to ensure that solutions are realistic, accurate and applicable by the driver. The use of this algorithm provides energy savings and, in addition, it permits railway operators to balance energy consumption and risk of delays in arrival. This way, the energy performance of the system is improved without degrading the quality of the service.