基于模糊推理的舰炮故障检测方法研究

基于模糊推理知识和模糊神经网络的理论,根据舰炮运转时发出的声音信号,提出了舰炮系统的故障检测诊断方案,详细介绍了信号提取的方法和故障分析的算法.     

IIR系统的自适应横向滤波辨识

用自适应线性组合器匹配IIR型离散系统,通过拟合系统传递函数来辨识系统参数;比较了该法与自适应递归算法的动态性能,数值仿真结果证明该法的有效性.     

ARMA谱估计在导弹仿真系统数学模型验证中的应用

针对反坦克导弹系统动态过程仿真的输出具有短时序、低信噪比的特点 ,研究了应用ARMA谱估计验证导弹系统仿真模型有效性的方法 ,并结合某型号滚转稳定的反坦克导弹系统复杂模型的仿真数据和简化模型的仿真数据给出ARMA谱估计的应用结果。     

多种武器攻击下舰艇装备生命力的加权模糊综合评估

通过应用模糊数学理论中模糊评估法对舰艇装备系统生命力进行了模糊评判 ,建立多武器攻击下舰艇装备生命力加权模糊评估模型 ,并以某舰艇装备的主动力系统回路为例 ,运用所建立的评估模型对其生命力进行具体评估 ,结果分析表明根据加权模糊综合评判模型 ,选用合理的加权系数 ,就能把模糊性很强的装备生命力指标定量化 ,为设备系统设计方案选优提供依据。     

雷达情报特征的Bayes识别方法

根据雷达情报目标判性应用背景,对Bayes方法在该领域的应用进行了研究,初步建立了基于雷达情报特征的统计模型,并在算法的收敛速度和稳健性等方面与D-S证据理论进行了比较。仿真结果表明,Bayes方法对先验信息的精确程度要求并不十分严格,能较好地解决雷达情报综合问题。     

C3I系统中的态势关联技术

态势关联是在态势估计前必须解决的一个问题,即要将不同时刻的态势数据进行关联,得到各个时刻态势数据中描述的目标间的关系。对时间间隔比较长的态势数据的关联,研究了一种基于模糊推理的态势关联方法,综合考虑了目标属性信息和状态信息、战场环境信息、指挥人员的态势预估计知识,通过推理得到关联的结果。     

X频段在地面警戒雷达中的应用特性

针对X频段在地面警戒雷达中的应用问题,在频段优势、对抗能力、机动能力方面,对X频段地面警戒雷达作了详细分析,同时论述了它在噪声背景和杂波背景下的性能、探测能力、系统特性,并提出了应采取的技术措施.通过实例表明该频段雷达具有一定的探测能力和抗干扰能力.     

Scheduling jobs with piecewise linear decreasing processing times

We study the problems of scheduling a set of nonpreemptive jobs on a single or multiple machines without idle times where the processing time of a job is a piecewise linear nonincreasing function of its start time. The objectives are the minimization of makespan and minimization of total job completion time. The single machine problems are proved to be NP‐hard, and some properties of their optimal solutions are established. A pseudopolynomial time algorithm is constructed for makespan minimization. Several heuristics are derived for both total completion time and makespan minimization. Computational experiments are conducted to evaluate their efficiency. NP‐hardness proofs and polynomial time algorithms are presented for some special cases of the parallel machine problems. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 531–554, 2003     

The stochastic single resource service‐provision problem

The service‐provision problem described in this paper comes from an application of distributed processing in telecommunications networks. The objective is to maximize a service provider's profit from offering computational‐based services to customers. The service provider has limited capacity and must choose which of a set of software applications he would like to offer. This can be done dynamically, taking into consideration that demand for the different services is uncertain. The problem is examined in the framework of stochastic integer programming. Approximations and complexity are examined for the case when demand is described by a discrete probability distribution. For the deterministic counterpart, a fully polynomial approximation scheme is known 2 . We show that introduction of stochasticity makes the problem strongly NP‐hard, implying that the existence of such a scheme for the stochastic problem is highly unlikely. For the general case a heuristic with a worst‐case performance ratio that increases in the number of scenarios is presented. Restricting the class of problem instances in a way that many reasonable practical problem instances satisfy allows for the derivation of a heuristic with a constant worst‐case performance ratio. Worst‐case performance analysis of approximation algorithms is classical in the field of combinatorial optimization, but in stochastic programming the authors are not aware of any previous results in this direction. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

态势估计中的二维模糊空间知识处理

空间推理是态势估计中的一个重要组成部分。针对海战态势估计的要求,建立了模糊确定性下二维空间点、区域,以及几种对态势估计中常用的空间关系的数学模型和用来确定空间关系的计算方法。