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471.
This article studies the problem of designing Bayesian sampling plans (BSP) with interval censored samples. First, an algorithm for deriving the conventional BSP is proposed. The BSP is shown to possess some monotonicity. Based on the BSP and using the property of monotonicity, a new sampling plan modified by the curtailment procedure is proposed. The resulting curtailed Bayesian sampling plan (CBSP) can reduce the duration time of life test experiment, and it is optimal in the sense that its associated Bayes risk is smaller than the Bayes risk of the BSP if the cost of the duration time of life test experiment is considered. A numerical example to compute the Bayes risks of BSP and CBSP and related quantities is given. Also, a Monte Carlo simulation study is performed to illustrate the performance of the CBSP compared with the BSP. The simulation results demonstrate that our proposed CBSP has better performance because it has smaller risk. The CBSP is recommended. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 604–616, 2015 相似文献
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现代战争的信息化程度、复杂性和不确定性不断提高,对海上远程精确打击(LPSS)体系作战能力的评估提出了更高的要求.要想准确评估系统的作战能力,建立合理的LPSS体系作战能力评估指标体系非常关键.然而影响LPSS体系作战能力的指标繁多,指标间存在冗余和相关性,不同层次指标间还存在交叉性,直接采用这些指标会增加后续评估的时空复杂度.在创建LPSS体系作战能力评估指标体系的基础上,对评估指标空间的建模方法进行研究,创建了可供评估的数据样本空间,为后续对底层指标集合进行约简、降维处理奠定了基础. 相似文献
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《防务技术》2022,18(9):1697-1714
To solve the problem of realizing autonomous aerial combat decision-making for unmanned combat aerial vehicles (UCAVs) rapidly and accurately in an uncertain environment, this paper proposes a decision-making method based on an improved deep reinforcement learning (DRL) algorithm: the multi-step double deep Q-network (MS-DDQN) algorithm. First, a six-degree-of-freedom UCAV model based on an aircraft control system is established on a simulation platform, and the situation assessment functions of the UCAV and its target are established by considering their angles, altitudes, environments, missile attack performances, and UCAV performance. By controlling the flight path angle, roll angle, and flight velocity, 27 common basic actions are designed. On this basis, aiming to overcome the defects of traditional DRL in terms of training speed and convergence speed, the improved MS-DDQN method is introduced to incorporate the final return value into the previous steps. Finally, the pre-training learning model is used as the starting point for the second learning model to simulate the UCAV aerial combat decision-making process based on the basic training method, which helps to shorten the training time and improve the learning efficiency. The improved DRL algorithm significantly accelerates the training speed and estimates the target value more accurately during training, and it can be applied to aerial combat decision-making. 相似文献
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分析了传统的灭火作战方案优选方法存在的弊端,提出了基于模糊集理论的计算理想点距离的优选法,明确了语言变量与模糊集理论的相关定义,规定了模糊评价语言与三角模糊数的换算方法,阐述了理想点距离的计算方法,建立了灭火作战方案优选模型,验证了该方法在灭火作战方案优选方面的科学性、有效性以及合理性. 相似文献
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陆军作战仿真是一个复杂的系统工程,仿真所涉及的模型种类繁多、类别不一。针对当前陆军作战仿真模型开发不规范、通用性与可重用性差、开发和集成效率低的现状,在对陆军作战仿真模型构成要素进行分析和归纳的基础上,提出仿真模型组件化设计的建模方法、采用"方案-单元-实体-组件"方式的模型管理机制以及采用事件驱动、事件订购和分发方式的模型交互机制。 相似文献