神经网络自适应给水控制器设计研究

针对船用核动力装置运行的特点,研究了直流蒸汽发生器的水位控制问题.利用现代控制理论,设计神经网络自适应给水控制器的结构和算法.仿真试验分析验证了神经网络自适应控制器的控制性能和可行性.     

汉语原型句蜕向英语多元逻辑组合的变换

汉语原型句蜕的英译形式多种多样,其中变换成英语的多元逻辑组合是涉及比较复杂变换细节的一种,因而成为颇具特色的语义块构成变换子类.文章从概念阐释入手,详尽分析了这种变换的语言现象、变换的必要性以及实施变换的技术准备.     

讲授《马克思主义哲学原理》课的几点思考

激发学生学习《马克思主义哲学原理》的兴趣,调动学生积极性,改进教学效果应做到:一结合历史、联系现实;二借助电教多媒体;三构建知识网络框架;四是运用互动式教学。     

分布式网络化测试系统设计

以某大型复杂装备远程测试系统为例,给出了基于DCOM的分布式网络化虚拟仪器测试系统的体系结构.该网络化测试系统体系结构采用DS技术作为客户端和测试端连接的中间件,并采用C/S、B/S混合模式使系统各COM/DCOM组件通过网络实现"无缝"连接.DCOM技术的应用使得各网络测试节点成为服务的本体,可以响应不同客户的测试需求,实现了良好的数据传输、安全管理和远程仪器控制.DS技术的使用进一步简化了计算机和测试应用之间的数据交换,达到了良好的实时传输效果.     

灭雷具图像声纳可视化仿真方法

介绍了一种灭雷具上高分辨率图像声纳对目标成像显示的计算机可视化仿真方法.此方法不是针对为声纳硬件的研制或调试而提供计算机辅助设计,而是从为部队官兵提供模拟训练平台的角度出发,提出一种数学模型和物理模型相结合的建模思路.同时也简单地介绍了仿真系统中三维海底地形和目标的数据模型.     

基于采样卡尔曼滤波的水下被动目标跟踪

针对水下被动目标跟踪问题中,采用直角坐标系容易出现滤波发散,而修正极坐标系下过程模型强非线性的问题,研究了一种修正极坐标系下的采样卡尔曼滤波算法.采样卡尔曼滤波比传统的扩展卡尔曼滤波更好地逼近状态方程和测量方程的非线性特性,给出更精确的均值和协方差的估计,并且适用于过程噪声与状态估计非线性耦合的情况.在修正极坐标系下,采用3种滤波方法求解被动目标跟踪问题,仿真结果表明,采样卡尔曼滤波的滤波精度优于传统的扩展卡尔曼滤波方法和自适应扩展卡尔曼滤波方法.     

基于BP神经网络装甲车辆电气设备故障诊断的研究

研究了装甲车辆电气设备故障的智能诊断,设计了基于BP网络的故障智能诊断系统。采用C8051F040单片机完成数据的采集和预处理,上位机应用C+ +builder和MATLAB的混合编程完成故障利用BP网络的诊断过程。研究结果表明,提高了设备故障诊断的准确度,实现了装甲车辆电气系统故障诊断的自动化、智能化。     

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.     

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。