地铁车辆安全疏散性能的仿真研究

从正在运行的北京地铁某型号车辆的空间布局特点出发,在现有的元胞自动机模型和行人流模型基础上,运用人员动态调整自身速度、动态调整自身运动方向等技术,建立了一种基于车辆环境约束以及人员行为特性的元胞自动机模型,该模型具有人员速度可变、能复现人员自组织现象的特点。论文以北京地铁某型号车辆为仿真对象,对车辆不同布局对车辆人员安全疏散性能的影响进行了计算机仿真并加以分析,提出改进建议。     

基于多智能体的自主移动机器人混合式体系结构

针对自主移动机器人系统的设计需求提出了一种基于多智能体的混合式体系结构,统一规划了机器人系统的软硬件结构,在该体系结构中设计并实现了硬件接口、慎思式和反应式三种智能体,提出使用多样化的信息组织形式,增强了系统的自适应能力和易扩展性。在具体的物理实现上采用了基于CAN总线的控制结构,并对各组成部分给出了详细的描述。测试结果证明了本移动机器人系统设计的可行性和高效性。     

基于多agent系统的舰艇编队防空辅助决策系统

提出基于多agent系统(multi-agent system,MAS)技术的分布式编队防空辅助决策系统基本框架。在目标信息共享和平台间实时作战参数交换的前提下建立了基于平等协商的分布式目标协商算法,混合运用Ta-bu搜索算法和基于规则的计划算法。在目标分配协商中,采用~Brown算法通过agent之间平等协商进行目标分配。在本舰防空计划中,采取软/硬防空计划并行比较消解冲突,实现本舰软/硬防空武器防空计划的协调。     

Multi-agent consensus with time-varying delays and switching topologies

The consensus problems of multi-agents with time-varying delays and switching topologies are studied. First, assume that an agent receives state information from its neighbors with fixed communication delays and processes its own state information with time-varying self-delay respectively. The state time-delay feedback is introduced into the existing consensus protocol to begenerate an improved protocol. Then a sufficient condition is derived which can make the system with time-varying self-delays achieve the consensus. On this basis, a specific form of consensus equilibrium influenced by the initial states of agents, time-delays and state feedback intensity is figured out. In addition, the multi-agent consensus is considered with time-varying topologies. Finally, simulations are presented to il ustrate the validity of theoretical results.     

实验经济学中多主体博弈仿真框架研究

在实验经济学中,为了研究有限理性行为,提出构建一种基于有限自动机的多主体博弈仿真框架。在该框架中采用有限自动机表示组织和个人行为,采用面向对象的可视化界面控制技术构造有限自动机,利用人工智能中的语言翻译技术把有限自动机翻译成线程,并对线程采用串行调度和并发调度的方式来实现多主体的序贯博弈、混合博弈及演化博弈。在博弈过程中采用遗传算法产生新的有限自动机。最后仿真了三人囚徒困境重复博弈中的战略演化过程。     

公共场所疏散引导人静态布局优化算法及其应用

采用最大覆盖选址问题的求解思路,提出了公共场所疏散引导人静态布局优化的拉格朗日松弛算法.结合引导人静态布局的特点,重点探讨了考虑和不考虑公共场所中被疏散人员分布状况的两种情况下的优化布局,并在MA-ESM模型的支持下,通过与人为布设引导人方式的模拟结果进行对比,评价了这两种优化布局的模拟效果。结果表明:引导人静态布局的优化不仅有利于充分发挥每个引导人的作用,提高疏散效率,而且可以确定布设引导人的最佳位置和特定公共场所中所需引导人的最大数量;同时考虑公共场所内被疏散人员分布状况下的优化布局能够有的放矢地调度引导人,提高引导效率。     

多Agent虚拟环境中的行为建模及其动画表现

多Agent虚拟环境是由多个Agent复杂多样的行为交互作用组成的分布式虚拟环境,它要求能够产生具有高度的沉浸感、可交互的环境,特别是环境中Agent所表现出来的行为必须具有足够的真实感,这一要求充分体现在针对分布交互仿真领域的计算机生成兵力(CGF)的研究中。本文基于此,提出了一个多agent行为建模方法,它支持可重用、可扩展,同时行为动画易于实现。     

多出口建筑物突发事件应急疏散模型和算法

建筑物内部一旦发生火灾等突发事故,需要以最快的速度把室内人员转移到建筑物外部.在考虑路径容量受限的多出口建筑物的疏散问题时,利用最短路径尽可能饱和疏散的思想,设计出可行疏散路径算法,通过对网络进行不断更新来确定每条路径实际流量,从而确定最优疏散方案最后通过算例验证了该算法的有效性和可行性.     

A message-driving formalism for modeling and simulation of multi-agent supply chain systems

To acquire a competitive advantage in the expanding market, manufacturing enterprises should be able to manage their supply chains as effectively as possible. It is now becoming popular to model supply chains as multi-agent systems and use discrete event simulation to learn more about their behaviors or investigate the implications of alternative configurations. In order to enhance the computational efficiency and keep the simulation credibility, this paper proposes a message-driving formalism for the simulation of multi-agent supply chain systems. Through the message-driving formalism, the problem of shared variables is addressed and the parallel operation of agents is implemented. Simulation experiments with a prototype implementation show that the message-driving formalism is able to provide credible results in significantly less simulation time.     

基于ExSpect语言的维修过程建模与仿真

研究了单部件可修系统的最优维修更换问题,构建了系统维修更换的Petri网模型,然后利用ExSpect仿真软件进行模拟仿真,从而证明了利用Petri网分析和解决系统维修更换问题的有效性。假定系统每次故障时以概率p进行更换及以概率1-p进行维修,并且每次维修后系统均不能“修复如新”,以系统的故障次数N为策略,利用几何过程建立数学模型,求出最优策略N*,使得系统经长期运行单位时间内期望损失达到最小,并求出系统经长期运行单位时间内期望损失的明显表达式。最后,对所得结果进行了讨论。     

n阶系统的fuzzy推理建模方法研究

把fuzzy推理建模法用于对一般n阶系统的建模中,分别建立了研究对象的输入输出型模型和状态空间型模型.在此基础上,对fuzzy推理建模法做了进一步的推广,分别选用梯形和"三角波"型fuzzy集隶属函数构造系统的微分方程模型,并通过仿真试验对两种模型进行了比较.     

复杂系统基于定性关系的建模与诊断推理研究

为克服复杂系统定量建模与诊断过程中存在的计算复杂、实时性和鲁棒性不强等缺陷,提出了基于定性关系模型的建模和诊断推理方法,研究并解决了其中的定性建模技术、定性推理方法及诊断机制等问题,并基于某空间飞行器推进系统进行了建模与诊断推理实例分析。验证结果表明,该方法具有建模方便、诊断快速等特点,为建立具有良好鲁棒性、实时性和实用性的诊断推理系统,提高复杂系统的可靠性提供了一条新的途径。     

大型复杂人机系统结构、过程建模与组织设计方法研究现状与展望

大型复杂人机系统是人类组织与人工系统构成的开放、动态、复杂的有机整体.本文分析了大型复杂人机系统研究的背景及意义,从结构、过程和组织三个视角总结了相关领域的研究进展,对未来大型复杂人机系统结构、过程建模与组织设计方法的主要研究方向及关键科学问题进行了展望.     

A multiscale modeling approach incorporating ARIMA and anns for financial market volatility forecasting

The financial market volatility forecasting is regarded as a challenging task because of irreg ularity, high fluctuation, and noise. In this study, a multiscale ensemble forecasting model is proposed. The original financial series are decomposed firstly different scale components （i.e., approximation and details） using the maximum overlap discrete wavelet transform （MODWT）. The approximation is pre- dicted by a hybrid forecasting model that combines autoregressive integrated moving average （ARIMA） with feedforward neural network （FNN）. ARIMA model is used to generate a linear forecast, and then FNN is developed as a tool for nonlinear pattern recognition to correct the estimation error in ARIMA forecast. Moreover, details are predicted by Elman neural networks. Three weekly exchange rates data are collected to establish and validate the forecasting model. Empirical results demonstrate consistent better performance of the proposed approach.     

供应链环境下核心企业系统的混合动态建模与仿真

系统动力学方法和基于Agent建模方法单独应用于供应链系统或企业系统建模都存在一定局限性。在详细分析了供应链环境下核心企业系统混合建模的必要性的基础上,提出了在核心企业内部考虑混合建模的基于多Agent系统和系统动力学方法的混合动态模型,可供供应链各实体间以及核心企业系统内部各部门间的相互作用及其耦合的分析;解决了JADE软件环境下系统集成仿真的关键技术;对该模型的仿真结果进行了初步分析,验证了供应链及其核心企业系统混合动态建模的可行性。     

Intelligent control over chaos in the rolling process and its comparison with tracking control

Some existing methods for chaos control in engineering fields are analyzed and their drawbacks are pointed out. A tracking method can solve these problems to some extent, but it still depends on the mathematical model of the system to be controlled. An intelligent method based on fuzzy neural network (FNN) is used to control chaos in engineering fields. The FNN is employed to learn the inherent dynamics from the input and output of chaos, which can be used in the inverse system method, so that the method is free of the exact mathematical model of the system to be controlled. This intelligent method is compared with tracking method in the presence of measurement noise and model error. Simulation results show its superiority and feasibility.     

基于k-近邻互信息的前向式变量选择方法及在水质参数软测量中的应用

软测量技术通过构造易测量的辅助变量与难测量的主导变量间的数学模型,实现对难测变量的实时预测.为有效分析辅助变量间的相关性和冗余性并实现变量精选,本文提出了一种基于k-近邻互信息的前向式变量选择方法.该方法以变量前向累加互信息值最大化为准则选择相关变量,同时计算每次累加变量与已选择变量子集间的互信息值来判断所累加变量是否为冗余变量,通过设定冗余互信息阈值,实现冗余变量的剔除,得到最优辅助输入变量子集.基于数值案例仿真结果验证了本文所提变量选择方法的可行性与有效性,在准确选取辅助变量的同时降低了算法复杂度.最后,该方法成功应用于污水处理过程中出水生化需氧量(biochemical oxygen demand,BOD)预测模型的输入变量选择上,利用精选出的辅助变量有效提高了模型预测精度.     

基于模糊综合评价的机械化挤奶站设备及配套方案选择研究

合理选择设备、科学制定设备配套方案是机械化挤奶站建设的关键。综合考虑了技术性能、经济性能和质量性能,利用专家打分、AHP分析和模糊综合评价方法,对挤奶机、牛奶冷却罐和挤奶厅供热装置的投资利用效果进行了评价,据此提出了东北农区机械化挤奶站设备选择及配套方案的建议,即提桶式挤奶机、进口牛奶冷却罐和热风式挤奶厅供热装置的组合。图2,表7,参3。     

面向应用领域的知识系统建模及实现

针对知识系统建模过程中不同类型知识的组织、表示、控制和实现等问题,将用户需求作为重要的切入点,通过对用户的需求分析和分解将知识系统数据结构划分为领域概念知识(概念本体)、领域系统知识(方法本体)、需求分解知识(需求本体)、知识系统控制知识和解释知识5大部分,建立了各部分的数据结构,明确了相互之间的关系。提出了基于层次案例规划(hierarchicalcase basedplanning,HCBP)的需求本体建立检索及面向目标的黑板控制结构和改进算法。实例测试表明,该方法不仅有利于不同类型知识块的重用,而且提高了系统的执行效率,大大缩短了知识系统的开发周期。     

New method for detection fusion of MAC based on DCM and NP rule

The problem of distributed detection fusion using multiple sensors for remote underwater target detection is studied. Considering that multiple access channel (MAC) schemes are able to offer high efficiency in bandwidth usage and consume less energy than the parallel access channel (PAC), the MAC scheme is introduced into the underwater target detection field. The model of underwater distributed detection fusion based on MAC schemes is established. A new method for detection fusion of MAC based on deflection coefficient maximization (DCM) and Neyman-Pearson (NP) rule is proposed. Under the power constraint of local sensors, this paper uses the DCM theory to derive the optimal weight coefficients and offsets. The closed-form expressions of detection probability and false alarm probability for fusion systems are obtained. The optimal detection performance of fusion systems is analyzed and deeply researched. Both the theory analysis and simulation experiments indicate that the proposed method could improve the detection performance and decrease the error probability effectively under power constraints of local sensors and low signal to noise ratio.