基于遗传算法的光电干扰资源优化分配研究

结合光电信息系统作战运筹中目标分配原则，及军事运筹理论，建立了干扰资源优化分配模型。给出了基于遗传算法的模型求解方法及步骤，阐述了遗传算法在光电干扰资源分配中的应用，并进行了实例仿真，得出了最佳干扰资源分配方案。仿真结果证明，该方法对于约束条件复杂的优化模型求解是有效、可行的，为光电信息系统指挥控制决策提供了有力支持。     

美军战术互联网构成及其战术模拟方法研究

分析了美军战术互联网的功能、特点及组成。结合现有战术互联网模拟系统提出了一种战术模拟方法,并说明了该方法中网络构建和业务规划的过程。利用海军陆战队战术互联网运用案例详细介绍了该模拟方法中网络构建模拟、战情构建模拟的主要过程。结果表明,该模拟方法对改进我军战术互联网,提高其运用以及在电子信息靶场开展战术互联网对抗训练及对抗技术研究中有重要的指导作用。     

基于多属性决策的相控阵雷达截获任务规划算法

作战管理是弹道导弹防御的核心,而作战管理的首要任务是雷达任务规划,雷达任务规划是一个多属性决策问题。通过对影响雷达截获目标的关键因素分析,提出以任务相对截止时间、目标优先级、目标距离时间等因素为核心,采用多属性决策方法,建立雷达截获任务优先级模型,实现雷达截获任务规划算法。仿真结果表明：文中提出的算法在雷达截获任务安排上合理、有效。     

面向战场的气象水文仪器仪表战备储备量分析

军用气象水文仪器仪表战储器材储备是战时气象器材战略支援前伸的储备,其所储备器材的品种、质量和数量都直接影响着战时气象保障率。从适应未来高技术局部战争的实际需要出发,针对我军近年来装备部队的主要新型气象仪器仪表装备,对其进行研究,以使气象仪器仪表装备储备器材在战时为气象保障提供持续、高效、稳定的器材保障,并为器材的优化配备奠定研究的基础。     

A New Fuzzy Adaptive Genetic Algorithm

Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper This algorithm is more effective in global search while keeping the overall population size constant. The simulation results of function optimization show that with the proposed algorithm, the phenomenon of premature convergence can be overcome effectively, and a satisfying optimization result is obtained.     

Improving group decision making: a fuzzy GSS approach

Group decision-making methods have been developed extensively, but their adaptation for use in organizations has been problematic. According to Arrow's (1963) Impossibility theorem, one conceivable reason is that a group decision outcome could never satisfy all decision makers' individual preferences. In order to accommodate individual decision maker's preferences in a group decision-making task, this correspondence presents a fuzzy multiperson multicriteria decision making (MMCDM) model and a structured group decision-making process. The fuzzy MMCDM model includes fuzzy individual preference generation and group preference aggregation. The structured decision-making process keeps the group interaction on track, so that the fuzzy MMCDM model can be effectively applied to the group decision-making task. Based on the proposed model and the decision-making process, a fuzzy group support system (GSS) has been developed and applied to a group assessment task. An empirical study was conducted and the experiment results showed that use of the fuzzy GSS enhanced individual understanding, consensus, and satisfaction of the group decision outcome     

基于遗传算法的战术飞行指令优化设计

通过对空战管理系统的关键组成部分－战术飞行指令生成系统的设计分析,针对其它设计优化方法的不足,提出利用遗传算法的方法优化战术飞行指仿,并通过仿真,证明了这一方法的有效性。     

云雾混合网络下基于多智能体架构的资源分配及卸载决策研究

针对D2D辅助的云雾混合架构下资源分配及任务卸载决策优化问题,该文提出一种基于多智能体架构深度强化学习的资源分配及卸载决策算法。首先,该算法考虑激励约束、能量约束以及网络资源约束,联合优化无线资源分配、计算资源分配以及卸载决策,建立了最大化系统总用户体验质量(QoE)的随机优化模型,并进一步将其转化为MDP问题。其次,该算法将原MDP问题进行因式分解,并建立马尔可夫博弈模型。然后,基于行动者-评判家(AC)算法提出一种集中式训练、分布式执行机制。在集中式训练过程中,多智能体通过协作获取全局信息,实现资源分配及任务卸载决策策略优化,在训练过程结束后,各智能体独立地根据当前系统状态及策略进行资源分配及任务卸载。最后,仿真结果表明,该算法可以有效提升用户QoE,并降低了时延及能耗。     

A novel heuristic simulation‐optimization method for critical infrastructure in smart transportation systems

A simulation‐based optimization is a decision‐making tool that helps in identifying an optimal solution or a design for a system. An optimal solution and design are more meaningful if they enhance a smart system with sensing, computing, and monitoring capabilities with improved efficiency. In situations where testing the physical prototype is difficult, a computer‐based simulation and its optimization processes are helpful in providing low‐cost, speedy and lesser time‐ and resource‐consuming solutions. In this work, a comparative analysis of the proposed heuristic simulation‐optimization method for improving quality‐of‐service (QoS) is performed with generalized integrated optimization (a simulation approach based on genetic algorithms with evolutionary simulated annealing strategies having simplex search). In the proposed approach, feature‐based local (group) and global (network) formation processes are integrated with Internet of Things (IoT) based solutions for finding the optimum performance. Further, the simulated annealing method is applied for finding local and global optimum values supporting minimum traffic conditions. A small‐scale network of 50 to 100 nodes shows that genetic simulation optimization with multicriteria and multidimensional features performs better as compared to other simulation‐optimization approaches. Further, a minimum of 3.4% and a maximum of 16.2% improvement is observed in faster route identification for small‐scale IoT networks with simulation‐optimization constraints integrated model as compared to the traditional method. The proposed approach improves the critical infrastructure monitoring performance as compared to the generalized simulation‐optimization process in complex transportation scenarios with heavy traffic conditions. The communicational and computational‐cost complexities are least for the proposed approach.     

Topology control of tactical wireless sensor networks using energy efficient zone routing

The US Department of Defense (DoD) routinely uses wireless sensor networks (WSNs) for military tactical communications. Sensor node die-out has a significant impact on the topology of a tactical WSN. This is problematic for military applications where situational data is critical to tactical decision making. To increase the amount of time all sensor nodes remain active within the network and to control the network topology tactically, energy efficient routing mechanisms must be employed. In this paper, we aim to provide realistic insights on the practical advantages and disadvantages of using established routing techniques for tactical WSNs. We investigate the following established routing algorithms: direct routing, minimum transmission energy (MTE), Low Energy Adaptive Cluster Head routing (LEACH), and zone clustering. Based on the node die out statistics observed with these algorithms and the topological impact the node die outs have on the network, we develop a novel, energy efficient zone clustering algorithm called EZone. Via extensive simulations using MATLAB, we analyze the effectiveness of these algorithms on network performance for single and multiple gateway scenarios and show that the EZone algorithm tactically controls the topology of the network, thereby maintaining significant service area coverage when compared to the other routing algorithms.     

Intelligent control of complex electrochemical systems with aneuro-fuzzy-genetic approach

This paper describes different hybrid approaches for controlling the battery charging process. The hybrid approaches combine soft computing techniques to achieve the goal of controlling the temperature of the battery during the electrochemical charging process. We have reduced the time required for charging a battery with the use of fuzzy logic, neural networks, and genetic algorithms. In the neuro-fuzzy-genetic approach, neural networks are used for modeling the electrochemical process, fuzzy logic is used for controlling the process, and genetic algorithms are used to optimize the fuzzy system     

飞机航路规划决策系统研究与开发

现代低空突防技术TF/TA2对飞机航路规划提出了新的要求,在研究战机任务规划、战术规划的基础上,设计了飞机航路规划决策系统,包括地形模拟、最优航路算法研究、航路决策、雷达辐射源库、火力威胁库的建立等。     

基于改进混合遗传算法的云资源调度算法

在云计算中,系统规模和虚拟机迁移数量都是十分庞大的,需要高效的调度策略对其进行优化。将云计算的任务分配抽象为背包求解问题,可通过遗传算法进行求解。传统的遗传算法具有局部搜索能力差以及早熟现象的缺点,本文采用遗传和贪婪相结合的混合遗传算法。针对混合遗传算法在资源利用率与能源消耗的收敛速度较慢问题,本文通过改进适应度函数,改变了适应度函数在不同染色体间的差异度,从而提高了染色体在选择算子中的择优性能。仿真结果表明,该方法能够有效提高混合遗传算法在云计算资源优化中的收敛速度。     

云计算环境下能量感知的任务调度算法

云计算环境下传统独立任务调度算法容易导致较高资源能耗或较大任务时间跨度.针对该问题,文中提出了两种能量感知的任务调度算法,并利用遗传算法并行化搜索合理调度方案.两种算法在搜索过程中,分别通过能耗时间归一和能耗时间双适应度方法定义适应度函数并进行个体选择.仿真结果表明,与单独考虑时间或能耗相比,这两种算法能够更有效地缩短任务执行时间跨度,降低资源能耗.     

基于优化的决策树算法在热轧工艺中的应用

决策树分类方法是一种非常有效的机器学习方法,具有分类精度高、对噪声数据有很好的健壮性以及形成树状模式等优点,对决策树算法的优化也主要是从分支属性的选择标准,对决策树的修剪,以及引入模糊理论、粗糙集理论、遗传算法和神经网络算法等几个方面进行优化。引入粗糙集理论中的属性重要性原理来对决策树进行优化,首先计算出每个条件属性对分类的重要度,然后根据重要度大小来对样本集进行一个筛选,在不损害分类准确率的同时减小决策树的规模。整个算法在Visual C++6.0环境下编程实现,并应用于热轧工艺模型中,通过对热轧数据的处理,验证了算法的有效性。     

遗传算法优化模糊控制器参数的方法研究

基于遗传算法对模糊控制器参数进行寻优,首先采用模糊规则,通过模糊推理的方法对二阶系统进行仿真实验,仿真结果表明系统动态响应超调小、调节时间短,具有良好的性能;然后采用遗传算法,按照ITAE准则对控制器的参数进行优化,仿真结果表明动态性能比模糊控制显著改善,显示出遗传算法对模糊控制器参数寻优的有效性和优越性。     

Evolutionary Computation:an Overview

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无人作战模拟仿真中的VV＆A

根据无人作战模拟研究、开发过程中分队级作战单位建模与仿真环节上所存在的VV&A问题,从军事建模的过程与军事工程技术的角度出发,将一般仿真过程中的VV&A技术与军事作战模拟的特点以及无人作战模拟的特殊性三者有机的结合在一起,深入的探讨了在无人作战模拟仿真过程中VV&A问题的解决办法以及实现过程。通过对无人作战模拟仿真中VV&A的研究与解决,为今后的作战模拟,特别是无人作战模拟中如何解决建模及仿真过程中所存在的类似问题提出了一套系统的、科学的实现办法,具有一定的理论及实践意义。对于我军无人作战研究的深入开展以及跨越式发展具有一定的参考价值。     

Evolutionary Computation：ao Overview

Evolutionary computation is a field of simulating evolution on a computer.Both aspects of it ,the problem solving aspect and the aspect of modeling natural evolution,are important.Simulating evolution on a computer results in stochastic optimization techniques that can outperform classical methods of optimization when applied to difficult real-world problems.There are currently four main avenues of research in simulated evolution:genetic algorithms,evolutionary programming,evolution strategies,and genetic programming.This paper presents a brief overview of thd field on evolutionary computation,including some theoretical issues,adaptive mechanisms,improvements,constrained optimizqtion,constrained satisfaction,evolutionary neural networks,evolutionary fuzzy systems,hardware evolution,evolutionary robotics,parallel evolutionary computation,and co-evolutionary models.The applications of evolutionary computation for optimizing system and intelligent information processing in telecommunications are also introduced.     

A computer simulation model for the evaluation of mobile radio systems in the military tactical environment

A computer simulation model, designed specifically for the analysis and evaluation of military mobile radio communication systems in the tactical environment is discussed. The algorithms and performance models used in the simulation model are briefly described, while statistical characteristics are derived analytically for a simplified scenario. Typical computer-generated histograms and distribution functions are presented for the more complex scenarios. The computer simulation model is shown to be an effective design tool for many different applications.