两种涡扇发动机部件特性自适应模型对比

发展了航空发动机自适应模型．并对以两种优化算法为基础的自适应模型进行了对比分析。两种模型以通用特性为基础运用优化方法,以发动机主要性能参数和过程参数偏差函数最小为优化目标,以部件特性耦合因子为被优参数,可以预测出不同飞行条件下的发动机风扇、压气机、燃烧室、高压涡轮、低压涡轮等部件特性。运用单纯形和遗传算法为基础的自适应模型对某型涡扇发动机性能的计算结果表明：相对于单纯形算法模型．遗传算法模型对发动机主要性能参数和过程参数的计算偏差降低了20％～30％;对发动机各截面总温、总压计算偏差降低了15％～20％;遗传算法模型相对于单纯形模型具有更为宽广的自适应模拟范围。对某型已知部件特性的涡扇发动机模拟结果显示．遗传算法模型部件特性模拟结果与已知部件特性差别甚微。     

一种基于多层SOFM网络的星图识别方法

提出了一种基于自组织特征映射(SOFM)神经网络的星图识别算法。用基于支持向量机(SVM)的动态阈值选取算法选取导航星构建导航星库,将一多层多个并联SOFM子网的识别系统用于星图识别。给出了方法的流程。仿真结果表明,SOFM网络可提取星图中的复杂特征识别导航星。与传统三角形算法相比,该识别算法的识别准确率、鲁棒性和实时性更优,有一定的实用价值。     

Seeing the Forest or the Trees? Shifting Categorical Effects in Map Memory

People use spatial and nonspatial information to structure memory for an environment. Two experiments explored interactions between spatial and social categories on map memory when mediated by retrieval (Experiment 1) and encoding (Experiment 2) demands. Participants studied a map depicting business locations (including proprietors' race). In Experiment 1, participants completed two memory tasks, one globally focused and the other locally focused. The global task compressed, while the local task expanded, within-category similarity. Furthermore, processing styles carried over to the subsequent task. Experiment 2 emphasized either the spatial or social category during encoding, which increased that category's weighting in memory. These results extend the work of Maddox, Rapp, Brion, and Taylor, suggesting that retrieval and encoding demands can shift how these categories affect spatial memory.     

Is Memory for Routes Enhanced by an Environment's Richness in Visual Landmarks?

We tested the hypothesis that a route's memorability is dependent on the frequency with which people are exposed to visual landmarks. Undergraduates learned either a route through an urban area lacking visually salient features, or a route in a neighborhood with many shops and urban objects. They were then asked to recall the learned route in the form of route directions and sketch maps. The results showed higher recall performance for the richer environment. When presented with photographs depicting scenes along the route, participants exposed to the richer environment had higher recognition scores and shorter response times than the others. The data confirm the functional role of landmarks in route memory and wayfinding.     

有人/无人机混合编队有限干预式协同决策

针对Leader-Follower异构型有人/无人机混合编队协同决策系统具有递阶分布式决策结构、决策信息分散以及通信约束等特点,在智能体模糊认知图(ABFCM)和动态模糊认知图(DFCM)的理论基础上,提出了一种有限干预式协同决策机制。通过构建层次化的Follower平台自主决策模型,实现了该平台与外部系统良好的交互能力,体现了自主决策的"动态性"。通过设计Leader平台的3种干预策略,满足了不同层次的决策需求,体现了干预过程的"有限性"。仿真结果表明:有限干预协同决策模型能够适应外部环境的动态变化,充分发挥Follower平台的自主决策能力;而不同层次的有限干预介入既减轻了Leader平台的控制负荷,又保证了决策的有效性和可行性,可为解决其他同类复杂系统的协同决策问题提供理论依据和方法参考。     

Design of transfer trajectories between resonant orbits in the Earth–Moon restricted problem

The application of dynamical systems techniques to mission design has demonstrated that employing invariant manifolds and resonant flybys enables previously unknown trajectory options and potentially reduces the ΔV$\mathrm{\Delta }V$ requirements. In this investigation, planar and three-dimensional resonant orbits are analyzed and cataloged in the Earth–Moon system and the associated invariant manifold structures are computed and visualized with the aid of higher-dimensional Poincaré maps. The relationship between the manifold trajectories associated with multiple resonant orbits is explored through the maps with the objective of constructing resonant transfer arcs. As a result, planar and three-dimensional homoclinic- and heteroclinic-type trajectories between unstable periodic resonant orbits are identified in the Earth–Moon system. To further illustrate the applicability of 2D and 3D resonant orbits in preliminary trajectory design, planar transfers to the vicinity of L₅ and an out-of-plane transfer to a 3D periodic orbit, one that tours the entire Earth–Moon system, are constructed. The design process exploits the invariant manifolds associated with orbits in resonance with the Moon as transfer mechanisms.     

基于双目视觉的类脑三维认知地图构建方法

基于大脑导航神经细胞机理的类脑认知地图构建方法,为发展智能同步定位与地图构建(SLAM)技术提供了新思路.针对现有类脑认知地图构建精度不高的问题,提出了一种基于双目视觉的类脑三维认知地图构建方法.首先阐述了类脑三维认知地图系统的工作原理,然后论述了不同视觉里程计对认知地图精度的影响,研究了基于双目视觉里程计的类脑三维认知地图精度优化方法,最终完成了基于视觉数据集的类脑三维认知地图构建试验.试验结果表明,所提方法构建的视觉里程计地图的三维位置误差为总行程的2.14％,认知地图的三维位置误差为1.56％;认知地图精度与里程计精度呈正相关;系统通过模板匹配进行回环检测与校正,提高了认知地图的精度.