应用遗传优化算法枚举结构系统的主要破坏模式

根据基因遗传算法的基本原理,提出了一种适用于枚举结构系统主要破坏模式的遗传优化算法,讨论并解决了该法实施过程中的编码技术、适合度函数定义、遗传操作方式等具体技术问题。算例表明：提出的遗传优化算法能够稳定有效地搜索出结构系统的主要破坏模式,从而为进行结构系统的可靠性分析提供了一种崭新的智能方法。     

高分辨率雷达目标一维距离像的编码识别算法

文中提出了一种高分辨率雷达目标一维距离像的识别算法。该算法借用图像处理方法,先对雷达目标的一维距离像进行编码,经过傅里叶变换提取一组形状特征。这组特征精确地描述了一维距离像曲线的走向。而后,利用人工神经网络技术对一定姿态角变化范围内的这组形状特征进行识别。实验结果表明,可以获得良好的识别效果。该算法为雷达目标一维距离像识别算法的实时处理提供了一条有效途径。     

求解特征结构配置问题的一种新方法

基于遗传算法提出了求解线性多变量系统在输出反馈作用下的特征结构配置问题的一种新方法。遗传算法是一种基于自然选择和群体遗传学机理的参数搜索方法。采用遗传算法求解特征结构配置问题,具有适用面广和计算稳定等特性。我们以导弹控制系统为例进行了仿真,结果是令人满意的。     

防空导弹垂直发射转弯优化设计的新方法

防空导弹采用垂直发射方式时 ,最重要的要求就是导弹发射后在最短的时间内以最小转弯半径完成程序转弯 ,所以是一个快速最优控制问题 ,文章对连续系统的最优控制进行离散化 ,从而应用遗传算法对防空导弹垂直发射转弯程序进行了优化设计     

基于遗传算法的协同多目标攻击空战决策方法

多机协同多目标攻击是未来空对空作战的一种重要形式。首先建立了多机协同空战的自主优势矩阵 ,并依据多人冲突决策理论构造了空战的总体优化指标向量 ,然后针对其他优化算法的不足 ,提出用遗传算法优化该指标向量 ,实现多机协同多目标攻击空战决策 ,最后对 2∶ 2空战进行了仿真。仿真结果证明了上述思想的正确性。     

A competitive genetic algorithm for resource-constrained project scheduling

In this paper we consider the resource-constrained project scheduling problem (RCPSP) with makespan minimization as objective. We propose a new genetic algorithm approach to solve this problem. Subsequently, we compare it to two genetic algorithm concepts from the literature. While our approach makes use of a permutation based genetic encoding that contains problem-specific knowledge, the other two procedures employ a priority value based and a priority rule based representation, respectively. Then we present the results of our thorough computational study for which standard sets of project instances have been used. The outcome reveals that our procedure is the most promising genetic algorithm to solve the RCPSP. Finally, we show that our genetic algorithm yields better results than several heuristic procedures presented in the literature. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 733–750, 1998     

Hamilton系统辛算法的Nekhoroshev稳定性分析

研究辛算法应用于Hamilton系统时的Nekhoroshev稳定性，利用辛映射的插值定理，得到了辛算法的插值定理，进而把它应用到凸Hamilton系统，得到了辛算法的Nekhoroshev稳定性，即辛算法在指数长时间内的稳定性。     

基于蚁群算法的被动目标定位算法

通过对蚁群算法的研究,用蚁群算法成功解决了无源测向定位中消除虚假点,对真实交点进行正确聚类的难题.并通过Matlab 仿真实验证明了该算法的有效性.同时该算法具有目标关联确率高、计算速度快、鲁棒性强等优点.     

The Cyprus puzzle and the Greek - Turkish arms race: Forecasting developments using genetically evolved fuzzy cognitive maps

The scope of this paper is to forecast the extent to which a settlement of the Cyprus issue may be possible given the decisions taken during the Copenhagen EU summit. It aims, in addition, at investigating the possibilities of improvement in Greek-Turkish relations which may lead, in turn, to reducing the arms race between the two countries. The paper uses a Genetically Evolved Certainty Neuron Fuzzy Cognitive Map algorithm to consider a number of scenarios examining the possible reactions of all sides involved in the Cyprus issue, namely Greece, Turkey, Cyprus, the Turkish-Cypriot community and the international environment. All simulation exercises suggest that the Greek and the Cypriot side should not necessarily rely on the decisions taken during the Copenhagen summit conference. The forecasts point out, in addition, that the optimism of the Greek government concerning the outlook of its relations with Turkey, and a subsequent reduction of the arms race against it, is far from being justified.     

基于遗传算法的雷达管控问题

通过对雷达组网系统责任区保障问题的深入研究,以完成对责任区的保障任务为目的,使责任区各个高度层均满足一定联合探测概率和雷达覆盖系数为约束条件,以雷达网整体工作代价最小为目标函数,构建了有干扰情形对雷达的管理和控制(以下简称雷达管控)数学模型。运用改进的遗传算法对雷达管控模型进行求解,通过设定保护概率保存了最优个体的遗传性,通过合理的算法参数设置改善了算法的性能。仿真算例和实际应用结果表明,雷达管控达标率由管控前的36.54%上升到63.46%,达到100%,雷达管控结果符合管控要求,且雷达开机数量较少,采取的抗干扰措施合理,验证了模型和方法的有效性。