Adaptive control of track tension estimation using radial basis function neural network

Track tension is a major factor influencing the reliability of a track. In order to reduce the risk of track peel-off, it is necessary to keep track tension constant. However, it is difficult to measure the dynamic tension during off-road operation. Based on the analysis of the relation and external forces depending on free body diagrams of the idler, idler arm, road wheel and road arm, a theoretical estimation model of track tension is built. Comparing estimation results with multibody dynamics simulation results, the rationality of track tension monitor is validated. By the aid of this monitor, a track tension control system is designed, which includes a self-tuning proportional-integral-derivative (PID) controller based on radial basis function neural network, an electro-hydraulic servo system and an idler arm. The tightness of track can be adjusted by turning the idler arm. Simulation results of the vehicle starting process indicate that the controller can reach different expected tensions quickly and accurately. Compared with a traditional PID controller, the proposed controller has a stronger anti-disturbance ability by amending control pa-rameters online.     

自然场景车标数据集的构建及其应用

车标作为车辆身份的关键特征之一,在车辆的监控与辨识中发挥着重要作用。由于自然场景复杂多变,对其中的车标进行准确识别仍具有很大的挑战性。目前公开数据库很少且存在诸多局限,导致研究缺乏可信度和实用性。本文建立了一个面向自然场景的全新数据集,包含多种采集环境下的10 324幅、67类车辆图像。基于此数据集开展应用研究,提出一个目标检测与深度学习相结合的车标识别方法,包括车标区域定位和车标种类预测两大步骤。实验表明,该方法对复杂背景有较强的适应性,在涉及30种车标的分类任务中达到89.0%的总体识别率。     

Predicting intensive care unit bed occupancy for integrated operating room scheduling via neural networks

In a master surgery scheduling (MSS) problem, a hospital's operating room (OR) capacity is assigned to different medical specialties. This task is critical since the risk of assigning too much or too little OR time to a specialty is associated with overtime or deficit hours of the staff, deferral or delay of surgeries, and unsatisfied—or even endangered—patients. Most MSS approaches in the literature focus only on the OR while neglecting the impact on downstream units or reflect a simplified version of the real‐world situation. We present the first prediction model for the integrated OR scheduling problem based on machine learning. Our three‐step approach focuses on the intensive care unit (ICU) and reflects elective and urgent patients, inpatients and outpatients, and all possible paths through the hospital. We provide an empirical evaluation of our method with surgery data for Universitätsklinikum Augsburg, a German tertiary care hospital with 1700 beds. We show that our model outperforms a state‐of‐the‐art model by 43% in number of predicted beds. Our model can be used as supporting tool for hospital managers or incorporated in an optimization model. Eventually, we provide guidance to support hospital managers in scheduling surgeries more efficiently.     

面向管理员的网络可生存性建模与计算

从网络系统安全评价和管理的角度出发,紧密结合可生存性定义和可生存性的四个特征属性,建立了面向管理员的网络可生存性量化模型;给出了该模型的算法流程;提出了面向管理员的网络可生存性计算公式,该公式中包括恢复率和系统状态转移矩阵的计算方法,反映出可生存性对网络空闲资源和恢复时间的要求;最后进行了面向管理员的网络可生存性计算的仿真实验,表明可以利用有限的网络资源实现高水平的网络可生存性。     

基于多元高斯概率分布的无线局域网定位方法研究

针对无线局域网环境及室内目标定位需求,研究了基于接收信号强度指示的定位技术,提出了一种基于多元高斯概率分布的信号强度模式匹配方法,讨论了定位系统框架。试验结果表明,该方法具有较好的室内定位效果。     

基于动态神经网络的装备技术状态预测模型

装备的技术状态受多种因素的影响,诸多影响因素之间是一种多变量、强耦合、非线性的关系,同时这种关系还是动态的。根据装备技术状态的特性,使其在相空间里重构,然后利用动态神经网络建立装备技术状态预测模型,并以装备振动信号预测为例进行案例研究,验证了利用动态神经网络进行预测的可行性和优越性。     

基于被动雷达和红外传感器的数据融合

提出基于被动雷达和红外传感器组成的复合探测系统,利用D-S证据理论提高目标识别率,借助神经网络改善目标跟踪算法的性能,同时保持跟踪滤波的计算结构尽可能简单,尤其是减少了数字计算上的复杂性。仿真结果表明了应用新算法的复合探测系统的有效性。     

信息化方式与人类社会形态

通过人类社会的几种基本形态组成形式与信息化方式的关系分析信息化方式对社会的影响问题,认为人类社会形态的具体表现形式与信息化方式的速度密切相关,社会形态单元的空间大小可以通过定量的方法给出;另外,还讨论了光速信息化方式对社会的影响、人工智能与信息化技术的关系、人类社会与机器网络社会的关系等问题。     

基于网络处理器的新型IPv6转发系统的设计与实现

转发与控制分离结构的提出和网络处理器的发展对路由器的扩展性、灵活性、性能具有重要的影响,而IPv6作为下一代互联网协议的核心,是路由器研究的重要对象。简要阐述了基于转发与控制分离结构ForCES的IPv6路由器的系统结构,重点论述了基于网络处理器的IPv6路由器的转发结构、双栈转发系统的流程设计和隧道机制设计的实现,给出IPv6路由器原型系统的实际测试结果。     

基于径向基神经网络的水下振动物体辐射噪声级别分类研究

运用径向基神经网络,利用水下振动物体内表面加速度信号对其辐射噪声级别进行分类,达到判断其声隐身性的目的.该方法的运算量较传统方法大大降低,极大地提高了计算速度.实例表明,该方法能较准确地对水下振动物体辐射声场声压级别进行分类,进而对其推广应用于潜艇提供了较好的依据.