铁路机车司机驾驶能力的心理学检验指标及其效标

应用检验空军驾驶能力的心理学指标——五项纸笔方法对铁路机车司机驾驶能力进行心理学检验，并用标准９分制进行校标，结果表明除曲线轨迹相关较差不宜应用外，其他四项均可应用。     

BOT项目融资风险的模糊综合评价方法研究

BOT是一种新兴的项目融资模式，其本身的特点决定项目公司必然会承担较大的风险。在项目投资决策中，风险的分析与评价是关键。此文分析了BOT项目风险的来源并运用模糊理论建立模糊综合评价模型，为项目公司在选择BOT项目时进行科学的投资决策提供参考。     

基于模糊神经网络间隔调速模型的研究

间隔调速控制是驼峰控制的重点,目前普遍使用的间隔调速算法是出口定速法,不能适应车辆行驶的动态过程,容易出现错误导致事故发生。为此,本文提出了一种基于模糊神经网络理论求得动态出口速度的模型,使用改进的误差反向传播学习算法进行学习,具有很好的自学习和自适应能力,能根据列车的溜放实际情况自动调整减速器出口速度。     

Fuzzy and adaptive fuzzy control for the automobiles' active suspension system

Two typical criteria for good vehicle suspension performance are their ability to provide good road handling and increased passenger comfort. The main disturbance affecting these two criteria is terrain irregularities. Active suspension control systems reduce these undesirable effects by isolating car body motion from vibrations at the wheels. This paper describes fuzzy and adaptive fuzzy control (AFC) schemes for the automobile active suspension system (ASS). The design objective is to provide smooth vertical motion so as to achieve the road holding and riding comfort over a wide range of road profiles. The efficacy of the proposed control schemes is demonstrated via simulations. With respect to the optimal linear quadratic regulator (LQR), it is shown that superior results have been achieved by the AFC.     

条码字符的模糊识别方法

在分析条码字符常规识别方法的基础上,针对因扫描倾斜角和扫描速度改度引起的首读率不高问题,提出了模糊识别方法。理论分析和抽样结果都表明,在硬件设备和印刷质量相同的条件下,该方法的识别首读率明显高于常规识别方法。     

一种基于模糊原理的碰撞危险度模型

基于“领域”概念和模糊原理，建立起一个用于确定船舶间碰撞危险度的数学模型。该模型不仅综合考虑了多种因素对碰撞危险度的影响，而且简便易行。通过模拟试验表明：本模型能够很好地反映出实际情况，具有较好的效果。     

机械系统的模糊—随机可靠性

本文从组成系统的单元出发,在同时考虑模糊性和随机性的基础上,提出了机械系统的模糊—随机响应、模糊—随机安全准则、模糊有效域和模糊—随机可靠度等基本概念,进而利用模糊数学的原理和方法,建立了机械系统模糊—随机可靠度计算的基本理论。     

工程项目评标中模糊综合评估法的应用研究

工程项目招标评标活动应当遵循公平、公开、公正、科学、择优的原则。评标工作是一个多指标、多属性的决策问题。此文运用模糊综合评价的方法,提出了对建设工程进行定量评价的模糊评价分析模型,希望为工程项目的评标工作提供一种科学适用的方法。该方法既能减轻评标工作量,又能克服目前综合评估法中打分不易操作的弊病。从而在方法上尽量保证了评标定标的科学性、客观性和合理性。     

Modelling behavioural rules for daily activity scheduling using fuzzy logic

The paper focuses on how trip time variability affects re-scheduling of daily activities. A delay in a trip or an early arrival can contribute to changes in the timing, location of the next activity, and to the deletion/addition of some activities. We propose the idea of using fuzzy logic rules to explain the effect of variability in travel time on the benefits perceived by an individual with the changes, and to model different actions that the individuals take in order to re-establish the steadiness of the existing timetable. The fuzzy model is used to handle the imprecision of the data which is unstructured text. The results show that large deviations in trip duration are more likely to induce significant changes in the timetable whereas small deviations are either ignored or translated into modified timing of the next activity. In choosing an action, greater importance is assigned to the flexibility of the following activity, to the magnitude of the trip time saving/delay, and to the duration of the next activity. Time savings are not favoured unless they can be readily transferred into additional activity time allocated to the next activity or to a new activity. The fuzzy rules based system is capable of predicting satisfactorily the strategy of coping with uncertainty in travel times and the satisfaction sensed with the change.     

基于模糊自适应PID控制的ATO系统控制算法

为了研究ATO系统控制算法的智能性和高效性,在传统PID算法的基础上,充分考虑到列车系统的非线性和复杂性,结合模糊控制理论能进行实时非线性调节的优点,提出了模糊自适应PID控制算法。并在Matlab/Simulink中建立了ATO系统的仿真模型和算法控制模块。将两种算法分别运用到ATO系统中,对目标速度曲线进行跟踪,从停车精度、追溯性、准时性、节能性、舒适性五个方面对二者的控制性能进行比较分析。仿真结果表明,将模糊自适应PID算法运用到ATO系统中,列车的控制性能能够很好地满足ATO系统的各个性能指标要求。