定向攻击水雷打击概率模型研究

根据定向攻击锚雷的工作原理,建立了其对水面目标打击概率的仿真数学模型,可用于定向区域攻击锚雷打击概率的蒙特卡洛法仿真.     

基于相关熵的MACH滤波器

最大平均相关高度(MACH:Maximum Average Correlation Height)滤波器是一种重要的基于相关的模式识别方法。滤波器由训练数据线性构造而成,具有良好的畸变容忍能力,在线性高斯噪声条件下具有理论最优性。为将算法适用于广泛的非线性、非高斯情形,本文引入一种新的度量函数相关熵,可隐性地将输入数据通过非线性变换映射到特征空间;并在新的空间中提出了基于相关熵的MACH滤波器构造方法。最后将此方法应用于合成孔径雷达(SAR:Synthetic Aperture Radar)图像目标分类进行了实验,在接收机工作性能曲线和峰值旁瓣比的比对中,本文算法的性能均有所提升。     

马尔可夫过程的k/N系统使用任务完成能力分析

研究了任务期间允许换件维修和备件供应时k/N系统的任务完成能力.首先,利用马尔可夫过程分析了k/N系统的状态转移过程,研究了k/N系统在特定维修保障策略下的运行过程.然后,以k/N系统固定任务时间内在正常状态停留时间的分布函数作为其任务完成概率模型,并通过全概率分解和更新过程的分析方法对任务完成概率进行求解.最后,利用任务完成概率模型在Matlab中绘制了任务完成概率随任务时间、任务量、备件携行数量以及备件平均供应时间的变化曲线,讨论并分析了对任务完成概率的影响.     

一类搜索型多对二随机格斗的获胜概率

研究搜索型多对二随机格斗战斗模型。假设格斗开始时A方有m件武器,B方有2件武器,B方处于隐蔽状态,格斗开始后B方可以直接对A方进行射击,A方需先搜索到B方后才能进行射击。双方各为同类武器,都是集火射击,所有开火都是独立的,每件武器开火射击直到毁伤对方才重新射击下一个目标。对搜索时间和毁伤间隔时间都服从一般分布的随机格斗模型,通过分析各状态的特征,利用状态概率分析方法和向后递归时间方法建立状态方程,求出了格斗处在各个状态的概率,并得到双方的获胜概率计算公式。     

Appointment scheduling at a multidisciplinary outpatient clinic using stochastic programming

The purpose of this paper is to investigate the problem of constructing an appointment template for scheduling patients at a specific type of multidisciplinary outpatient clinic called an integrated practice unit (IPU). The focus is on developing and solving a stochastic optimization model for a back pain IPU in the face of random arrivals, an uncertain patient mix, and variable service times. The deterministic version of the problem is modeled as a mixed integer program with the objective of minimizing a weighted combination of clinic closing time (duration) and total patient waiting time (length of stay). A two‐stage stochastic program is then derived to account for the randomness and the sequential nature of the decisions. Although it was not possible to solve the two‐stage problem for even a limited number of scenarios, the wait‐and‐see (WS) problem was sufficiently tractable to provide a lower bound on the stochastic solution. The introduction of valid inequalities, limiting indices, and the use of special ordered sets helped to speed up the computations. A greedy heuristic was also developed to obtain solutions much more quickly. Out of practical considerations, it was necessary to develop appointment templates with time slots at fixed intervals, which are not available from the WS solution. The first to be derived was the expected value (EV) template that is used to find the expected value of the EV solution (EEV). This solution provides an upper bound on the objective function value of the two‐stage stochastic program. The average gap between the EEV and WS solutions was 18%. Results from extensive computational testing are presented for the EV template and for our adaptation of three other templates found in the literature. Depending on the relative importance of the two objective function metrics, the results demonstrate the trade‐off that exists between them. For the templates investigated, the “closing time” ranged from an average of 235 to 275 minutes for a 300‐minute session, while the corresponding “total patient time in clinic” ranged from 80 to 71 minutes.