基于遗传算法的移动Sink数据采集信宿路算法

数据收集是部署无线传感网络WSNs(Wireless Sensor Networks)基本目的。而采用移动Sink方式收集节点数据是解决数据收集效率的有效措施。为此,提出基于遗传算法的移动Sink数据采集算法GMSDC(Genetic algorithm-based Mobile Sink Data Collecting)。GMSDC算法利用遗传算法求解最佳驻留点,再由这些驻留点构建Sink移动路径。仿真结果表明,相比于EDAMS算法,GMSDC算法增加了数据收集量。     

基于星型链路的飞行器高码率数据采集传输系统设计与实现

数据采集系统是飞行器遥测系统的关键组成部分,在高码率传输情况下防止出现数据误码率偏高和遥测参数精度恶化是十分重要的研究课题。针对采集传数据系统的多参数快速切换,在多种网络拓扑结构分析的基础上,设计了一种适用于飞行器上的星型链路高码率数据采集传输系统,消除了异源晶振频率漂移积累的时间误差。实践表明,该系统能有效地满足航天飞行器高码率数据隔离采集、存储、传输和故障隔离的要求,其隔离信号绝缘电阻在100MΩ以上,隔离采集精度不超过1%,以7Mbps码率传输时在约0.2个采样周期内可以快速稳定到采样电压值,实现大容量数据的高可靠采集和传输。     

Structural reliability analysis under evidence theory using the active learning kriging model

Structural reliability analysis under evidence theory is investigated. It is rigorously proved that a surrogate model providing only correct sign prediction of the performance function can meet the accuracy requirement of evidence-theory-based reliability analysis. Accordingly, a method based on the active learning kriging model which only correctly predicts the sign of the performance function is proposed. Interval Monte Carlo simulation and a modified optimization method based on Karush–Kuhn–Tucker conditions are introduced to make the method more efficient in estimating the bounds of failure probability based on the kriging model. Four examples are investigated to demonstrate the efficiency and accuracy of the proposed method.     

Energy Optimization in Multi-UAV-Assisted Edge Data Collection System

In the IoT (Internet of Things) system, the introduction of UAV (Unmanned Aerial Vehicle) as a new data collection platform can solve the problem that IoT devices are unable to transmit data over long distances due to the limitation of their battery energy. However, the unreasonable distribution of UAVs will still lead to the problem of the high total energy consumption of the system. In this work, to deal with the problem, a deployment model of a mobile edge computing (MEC) system based on multi-UAV is proposed. The goal of the model is to minimize the energy consumption of the system in the process of data transmission by optimizing the deployment of UAVs. The DEVIPSK (differential evolution algorithm with variable population size based on a mutation strategy pool initialized by K-Means) is proposed to solve the model. In DEVIPSK, the population is initialized by K-Means to obtain better initial positions of UAVs. Besides, considering the limitation of the fixed mutation strategy in the traditional evolutionary algorithm, a mutation strategy pool is used to update the positions of UAVs. The experimental results show the superiority of the DEVIPSK and provide guidance for the deployment of UAVs in the field of edge data collection in the IoT system.     

回收努力影响下循环物流包装库存策略优化

目的 解决循环物流包装放置混乱造成循环物流包装返回率低、循环物流包装运营成本增加的问题。方法 在循环物流包装库存模型中引入回收努力作为决策变量,建立非线性规划模型,分析循环物流包装的最优检查周期、购买周期和最优回收努力水平的决策问题,设计迭代算法进行求解。比较分销商投入回收努力与不投入回收努力情况下系统的总成本和决策变量。结果 包装的最优检查周期为2.78,最优购买周期为4.88,分销商最优努力水平为230.96,系统总成本降低了42%,循环物流包装的检查周期缩短了49%,购买周期缩短了13%。结论 在循环物流包装的应用中,加强对循环物流包装管理流程的培训力度有利于循环物流包装系统更有效的运行。     

Collection network design with capacity planning in reverse logistics: static and restricted-dynamic models

This study proposes two collection network design models that determine the locations and capacities of collection centres and the allocations of refuse at demand points to the opened collection centres: a single-period static model for time-invariant demands and a multi-period restricted-dynamic model for time-variant demands over a planning horizon. The capacities of collection centres are not given, but decision variables are used to obtain cost savings by minimizing surplus capacities. The maximum allowable distance between collection centres and demand points and the minimum recovery rates of collection centres are also considered. Two heuristics are proposed for each of the two problems after formulating them as integer programming models. Computational experiments were conducted on various test instances, and the results are reported. It is shown from the test results that the restricted-dynamic approach outperforms the static model significantly when the refuse demands are time variant. Finally, some managerial insights are derived.     

多特征融合的异视角目标关联算法

目标关联在协同多目标探测中具有重要意义,受视角变换等因素的影响,传统目标关联算法在异视角目标观测情况下效果较差。本文提出了一种基于拓扑特征与颜色特征融合的无人机协同侦查目标关联算法,通过利用无人机提供的位置、姿态及其搭载传感器获得的多维特征数据,提取出目标的拓扑特征及颜色特征,并通过D-S证据理论融合多维特征,完成对异视角目标群的关联。实验表明,这种算法框架能够有效帮助无人机完成对目标群的关联任务。     

一种太阳能集热系统集热量实时预测的混合建模方法

太阳能集热器的集热量受光照度、环境温度、风速等多种因素的影响,其预测模型很难从预测精度和实时性上同时满足用户需求。本文提出一种实时预测太阳能集热系统集热量的混合建模方法。该方法首先从能量守恒出发,根据热管式太阳能集热系统传热机理推导出集热量的理论模型,并把理论模型中的散热系数、透射率、吸收率等经验参数以及采光面积、散热面积等几何参数集总为模型的未知参数,进而提出混合模型的结构。然后,利用TRNSYS仿真软件搭建太阳能集热器模拟仿真系统,对仿真系统不同的运行工况进行仿真实验,获取用于辨识混合模型未知参数的稳态数据。最后,选用粒子群优化算法（PSO）作为模型参数的辨识方法,利用所获得的稳态数据辨识模型的未知参数。模型预测值与仿真实验结果的比较表明,预测模型简单而精确,能够在各种工况下实时地、高精度地预测太阳能集热器的集热量,其平均相对误差可达到2.02%。该模型在太阳能热泵、太阳能热水器等系统的优化控制领域得以广泛应用。     

一种低功耗高精度的NB-IoT温度采集系统设计

针对目前工业应用中对精度和功耗的要求,设计了一款以低功耗、高性能的PIC18F24K22单片机为处理器,以PT100为温度传感器,以高精度的AD7794为A/D转换器,利用NB-IoT通信模块进行无线传输的温度采集系统.设计中PT100采用四线制消除来自连接导线的压降误差,使用精密电阻法为AD7794转换电路提供参考电压,消除了恒流源漂移电流误差,同时减小了参考电压精度对测量结果的影响.设计了高精度的电阻值-温度值的变换关系式,有效地减少了转换误差.测试结果表明,温度的测量精度高于0.04 ℃,并且在实际的应用环境中具有出色的稳定性.     

移动支付在地铁互联网售票机系统中的应用

为丰富乘客的购票支付方式,提高出行体验,地铁自动售票机(TVM)系统引入移动支付功能具有一定的必要性。本文分析地铁互联网售票机的软件系统框架,对移动支付功能进行设计,提出移动支付与地铁自动售票机的结合形式和工作流程。根据本方案设计的互联网售票机已经应用到南京地铁自动售检票(AFC)系统中,通过测试验收,验证了该方案的可行性,对其他城市的地铁自动售票机移动支付功能的开发有着一定的参考意义。