RELATIONS BETWEEN PERFORMANCE POTENTIALS AND INFINITESIMAL REALIZATION FACTORS IN CLOSED QUEUEING NETWORKS

In this paper,the concept of the infinitesimal realization factor is extended to the parameter dependent performance functions in closed queueing networks.Then the concepts of realization matrix (its elements are called realization factors) and performance potential are introduced,and the relations between infinitesimal realization factors and these two quantities are discussed.This provides a united framework for both IPA and non IPA approaches.Finally,another physical meaning of the service rate is given.

Literature Review on Network Design Problems in Closed Loop and Reverse Supply Chains

The productivity of an organization is very much affected by non-value adding activity like logistics, which moves the resources from suppliers to factory, raw materials/semi-finished items within the factory and finished goods from factory to customers via a designated distribution channel called as forward logistics. In some cases, parts of the products such as automobiles, computers, cameras, mobile phones, washing machines, refrigerators, garments, footwear and empty glass bottles of beverages, etc. will be brought back to the factories as a product recovery strategy through reverse logistics network which is integrated in a sustainable closed loop supply chain network. So, it is highly essential to optimize the movement of the items in the reverse logistics network. This paper gives a comprehensive review of literature of the design of networks for the reverse logistics as well as for the reverse logistics coupled with forward logistics. The contributions of the researchers are classified into nine categories based on the methods used to design the logistics network.

ANALYSIS OF CLOSED DIELECTRIC WAVEGUIDES——MULTIMODE NETWORK APPPOACH

The dispersion characteristics of a class of closed dielectric waveguides are investigated by themethod which combines the building-block approach of multimode network theory with the rigorous modematching procedure.Several numerical examples for difrerent guiding structures have been given by the ap-proach.The same structures are also analyzed with the finite element method and the EDC method forcomparison.The calculations show that the present approach yields as highly accurate results as the finite ele-ment method while almost retaining the simplicity of the EDC method,and justify the utility of the presentmethod.

An Integrated Multi-Echelon Model for a Sustainable Closed Loop Supply Chain Network Design

The integration of entire supply and value chain into a closed loop network is gaining more importance in recent times in order to ensure a business to be economically and environmentally sustainable with the changing trends in business and social environments, growing environmental consciousness in the society and government legislations to protect the environment as well as the business. In this context, this paper considers a multi-echelon closed loop supply chain network design with forward and reverse logistics components. An attempt has been made to develop a mixed integer non-linear programming model for this problem with different costs so that the sum of the total cost is minimized subject to different constraints pertaining to capacities of the entities of the system, demands of first customers and second customers. A generalized model is presented and then its application is illustrated using an example problem by solving the model using LINGO14. This model forms as a tool to compare future meta-heuristics to check the closeness of their solutions with corresponding optimal solutions.

A closed-loop Supply Chain Network Equilibrium Model with Fuzzy Demand under Production Capacity Constraints and Price Rigidities

A closed-loop supply chain network equilibrium problem is examined,which consists of mutual competitive manufacturers with production capacity constraints and retailers with fuzzy market demands,mutual competitive collectors as well as a binding price ceiling of the commodities.By utilizing the credibility measure of fuzzy event,variational inequality and Lagrange dual theory,the optimum behaviors of manufactures,retailers,collectors and consumers are described.Therefore,the supply chain network equilibrium model is established.Numerical examples were given to illustrate the impact of production capacity constraints and price ceiling on the network equilibrium pattern.The results show that the shortage of commodities in consumer market will be more serious,the wholesale price of product and purchase price of waste products rise,the profits of retailers decrease,the profits of manufacturers and collectors increase as the government gradually reduce the binding price ceiling on competitive markets,and the trend will be more obvious in the existence of production capacity constraints at same time.

贸易政策不确定性与技术创新——基于贸易网络的调节效应

随着全球贸易保护主义趋势不断加强,各国的贸易政策不确定性也在不断增加。文章基于2008-2019年79个国家的相关数据,实证分析了贸易政策不确定性对技术创新的影响。研究结果表明:由贸易政策干预所引起的贸易政策不确定性的增加,不利于受影响国技术创新水平的提高;相较于发达国家,发展中国家技术创新受贸易政策不确定性的影响更为显著;贸易政策不确定性的增加不利于受影响国技术创新水平的提高,但受影响国可以通过提高自身的贸易网络地位,减弱贸易政策不确定性对技术创新的负面影响。在全球贸易保护主义趋势不断加强的背景下,各国应根据国情制定相关政策,积极推动国家间经济合作的达成来应对贸易政策不确定性所带来的影响。

基于神经网络的零射程线闭路制导方法

对于固体发动机飞行器,在动力飞行段一般采用能量匹配闭路制导或者倾角约束的闭路制导方法,这种闭路制导方法的控制精度较高,但其精度受到发动机性能偏差的影响较大,为了减小发动机性能偏差对制导精度的影响,提出了基于神经网络的零射程线闭路制导方法。首先,建立了飞行器动力飞行段运动模型,对零射程线闭路制导进行了分析推导;其次,设计了多输入神经网络算法,确定了输入输出参数,对剩余能量、待增速度以及趋零射程线角度进行训练,将神经网络训练结果与零射程线闭路制导相结合,使得在不同的发动机偏差情况下,反馈不同的趋零射程线角度;最后,通过选择不同的偏差状态进行仿真验证,仿真结果表明该方法能有效地减小发动机偏差对制导精度的影响,具有较强的抗偏差能力,制导精度高。

Development and Comparison of Hybrid Genetic Algorithms for Network Design Problem in Closed Loop Supply Chain

This paper presents four different hybrid genetic algorithms for network design problem in closed loop supply chain. They are compared using a complete factorial experiment with two factors, viz. problem size and algorithm. Based on the significance of the factor “algorithm”, the best algorithm is identified using Duncan’s multiple range test. Then it is compared with a mathematical model in terms of total cost. It is found that the best hybrid genetic algorithm identified gives results on par with the mathematical model in statistical terms. So, the best algorithm out of four algorithm proposed in this paper is proved to be superior to all other algorithms for all sizes of problems and its performance is equal to that of the mathematical model for small size and medium size problems.

Adaptive proportional integral differential control based on radial basis function neural network identification of a two-degree-of-freedom closed-chain robot

A closed-chain robot has several advantages over an open-chain robot, such as high mechanical rigidity, high payload, high precision. Accurate trajectory control of a robot is essential in practical-use. This paper presents an adaptive proportional integral differential （PID） control algorithm based on radial basis function （RBF） neural network for trajectory tracking of a two-degree-of-freedom （2-DOF） closed-chain robot. In this scheme, an RBF neural network is used to approximate the unknown nonlinear dynamics of the robot, at the same time, the PID parameters can be adjusted online and the high precision can be obtained. Simulation results show that the control algorithm accurately tracks a 2-DOF closed-chain robot trajectories. The results also indicate that the system robustness and tracking performance are superior to the classic PID method.

基于电机电流的高压断路器弹簧操作机构的LM-BP故障诊断算法

BP(back propagation)神经网络由于具有线性映射能力强及自适应能力强等优点,常被用于高压断路器弹簧操作机构的故障诊断中,但易陷入局部最小点限制了网络的收敛速度和分类精确度。文中提出了一种基于L-M算法优化BP神经网络的高压断路器操作机构故障诊断方法,分析了神经网络的数学模型及映射关系,运用L-M算法对传统BP网络进行优化,解决了传统BP神经网络梯度下降法存在局部最小化、易产生平坦区等问题,有效地提高了算法的训练速度,同时提高了分类的精确度。诊断结果表明:L-M算法优化后的BP神经网络能有效地实现高压断路器操作机构故障诊断。文中研究内容对高压断路器操作机构故障诊断提供了思路与方法,对提高高压断路器安全可靠性具有重要意义。

基于信息熵与闭合频繁序列的密码协议逆向方法

未知密码协议被广泛用于敏感信息的安全传输,对其进行逆向分析对攻防双方都具有重要意义。为从网络流量中推断结构复杂的密码协议格式,提出了一种基于信息熵与闭合频繁序列的密码协议逆向方法。利用字节信息熵划分报文的明文域与密文域,使用BIDE算法挖掘闭合频繁序列,划分报文的动态域和静态域;设计了一种长度域识别算法,对报文进行字节片切,将片切后的字段值与长度域取值集合进行循环比对,实现了密码协议中多种形式的长度域识别;设计了启发策略,用于对加密套件、加密算法等密码协议特有的关键字段进行语义识别。实验结果表明,该方法可以有效地对密码协议进行域划分,提取密码协议的格式,并且在长度域识别和密码协议特有关键字段的语义识别上优于现有方法。

合环转电对环网型美式箱变的影响研究

配电网合环转电的开展提高了供电可靠性,但合环电流对电网的冲击影响着配电网的安全稳定运行。从配电网生产运行中遇到的问题着手,通过现场试验、理论分析、仿真验证等方法分析了合环转电对环网型美式箱变的影响,为配电网倒闸操作、规划建设提出了合理建议。

基于双环自适应滑模控制的高速列车运行追踪

针对列车高速运行跟踪控制问题,提出了一种基于双环结构的RBF神经网络自适应滑模控制算法。首先系统结构分为位移与速度控制子系统,防止列车因单个控制器故障而失控;在此基础上采用积分滑模控制,加强控制器的鲁棒性;同时在速度子系统中引入参数自适应算法与RBF神经网络自适应算法削弱列车受到基本阻力、附加阻力以及不确定性阻力带来的影响;最后通过Lyapunov稳定性分析证明系统的稳定性。通过仿真实验结果表明,位移误差在[-3.3×10^(-4),1.9×10^(-4)]范围以内,速度误差在[-2.1×10^(-2),3.1×10^(-2)]范围以内,该算法可以实现对列车的速度与位移精确追踪。

极端气象灾害下考虑MESS主动调控的配电网故障恢复策略

针对极端灾害天气下配电网的故障恢复问题,计及极端灾害的时空演变特性,提出了一种利用移动储能(mobile energy storage system,MESS)的灵活性主动参与抑制合环冲击电流,辅助配电网故障恢复的策略。首先,建立了暴风雨等不同气象灾害条件下配电线路的故障率统计模型。其次,将复杂交通网与配电网进行耦合,建立了以最小化MESS调度时空成本的上层预布局模型。然后,分析了MESS出力对冲击电流的影响,以抑制合环冲击电流、最大化负荷恢复率和最小化MESS调度成本为目标,构建了MESS参与网络重构的下层调度模型。最后,在改进的IEEE 123节点系统中进行测试,验证了MESS对配网故障恢复安全性的提升效果。结果表明,采用MESS主动参与调控能够有效应对移动的极端气象灾害引发的配电网动态故障恢复问题,并抑制合解环过程中电流的波动,提升网络重构方案的可行性和增强配电网的韧性。

基于RBF神经网络的闭链下肢康复机器人自适应补偿控制

在下肢康复机器人的康复训练过程中,模型参数、环境干扰等不确定性因素会影响机器人轨迹跟踪的精度。针对这一问题,提出了一种基于径向基函数(Radial Basis Function,RBF)神经网络的自适应补偿控制,该控制方法能够提高机械系统轨迹跟踪的精确性。首先,设计一款具有4种工作模式、运动稳定的闭链卧式下肢康复机器人结构;然后,利用拉格朗日方法求解动力学名义模型,将康复装置的模型参数以及外界干扰等不确定性因素分离出来,并设计基于RBF神经网络的自适应补偿算法对其进行逼近控制;最后,通过Matlab/Simulink环境对其进行仿真验证,证明了该控制策略的有效性。结果显示,在人体步态曲线轨迹跟踪中,提出的基于RBF神经网络的自适应补偿算法相比传统的模糊比例-积分-微分(Proportional Integral Derivative,PID)控制的方法响应速度快、跟踪效果好,且髋关节和膝关节轨迹跟踪的角度误差峰值分别为0.08°和0.13°,远小于患者下肢在康复运动中的转动角度。设计了单腿样机试验,试验结果表明,采用的RBF补偿自适应控制器能够实现高精度的跟踪结果,也能够满足患者在康复训练中安全性的要求。

面向输变电场景的无线传感网通信性能测试研究

无线传感网在输变电设备状态监测领域的应用,能够有效提升电网运行效率,实现更高的经济价值和社会效益。通过分析无线传感网在输变电场景下的通信特征,提出通信性能测试方法,构建闭环测试平台,对无线传感网的接入容量、组网性能等关键指标开展测试验证。结果表明,所提测试方法能有效评估无线传感网的终端接入、数据传输能力,可为无线传感网在电力系统的推广提供技术支撑。

碳税政策下可持续双渠道闭环供应链网络优化设计

考虑到销售商具有渠道公平感知,因此引入利润公平分配理念,设计了碳税政策下的可持续双渠道闭环供应链网络模型。以经济成本最小、碳排放量最小、社会效益最大为优化目标,建立了结合双渠道特点的多目标混合整数规划模型,通过三角模糊数对模型不确定参数进行处理。运用NSGA-II算法对模型进行求解,得到单渠道、双渠道、考虑利润公平分配双渠道三种情形下的选址结果与流量分配。针对碳税价格、销售商的议价能力作灵敏度分析,从政府和企业层面给出相应的管理启示。

GNSS静态相对定位控制网同步环闭合差及重复基线较差限差研究

目前实际工程中,同步环坐标分量闭合差很难满足全球定位系统测量规范中的限差要求,而高速铁路工程测量规范中的同步环坐标分量闭合差限差又偏大,同时这两部规范所规定的同步环全长闭合差和重复基线长度较差限差也偏大。针对这一现象,本文基于基线解算完成后基线解算软件提供的方差协方差阵,推导了同步环坐标分量及全长闭合差限差和重复基线长度较差限差,并通过高速铁路某工程项目的CPII控制网的实测数据验证了上述限差的合理性。

基于神经网络的VSLAM综述

传统的基于视觉的SLAM技术成果颇丰,但在具有挑战性的环境中难以取得想要的效果.深度学习推动了计算机视觉领域的快速发展,并在图像处理中展现出愈加突出的优势.将深度学习与基于视觉的SLAM结合是一个热门话题,诸多研究人员的努力使二者的广泛结合成为可能.本文从深度学习经典的神经网络入手,介绍了深度学习与传统基于视觉的SLAM算法的结合,概述了卷积神经网络(CNN)与循环神经网络(RNN)在深度估计、位姿估计、闭环检测等方面的成就,分析了神经网络在语义信息提取方面的优点,以期为未来自主移动机器人真正自主化提供帮助.最后,对未来VSLAM发展进行了展望.

基于改进蜜罐算法的建筑材料闭环供应链网络优化模型

建筑材料闭环供应链网络优化是一个多目标的大规模问题,传统寻优算法易陷入局部最优无法求出全局最优解。因此,提出基于改进蜜罐算法的建筑材料闭环供应链网络优化模型。针对由业主、总承包商、分包商、分供方和其他合作机构组成的建筑材料闭环供应链网络结构,构建以最小化网络成本与最小化环境污染为目标、满足客户需求与流量平衡为约束的优化模型。采用一种基于混沌映射的改进蜜罐算法来求解模型,得到最优建筑材料闭环供应链网络优化方案。实验结果表明,所提改进蜜罐算法在求解建筑材料闭环供应链网络优化模型时搜索最优值优势明显,实现建筑材料闭环供应链网络最优。