多校区排课遗传算法设计

本论文分析了造成多校区高校排课困难的各种因素,研究了如何应用遗传算法来解决多校区高校排课困难的问题,并对该算法进行详细设计,给出了一个基于该算法的排课模型。     

拓扑自动发现中数据更新策略的研究

首先提出了在拓扑发现数据更新中的若干实际问题,然后对这些问题一一给出了解决方案,并提出一种基于状态的拓扑发现更新策略.最后,通过在一个比较大的局域网中的试验,在正确性和效率方面对该策略的性能进行了评价.      

邓小平实践思维方式初探

在独特的历史条件下,在我国社会主义建设的伟大实践中,邓小平形成了具有实践求实性、求同存异性、系统开放性和人民主体性等鲜明个性特点的实践思维方式。     

A D-optimal Multi-position Calibration Method for Dynamically Tuned Gyroscopes

This paper presents a novel experimental design to greatly improve the calibration accuracy of the acceleration-insensitive bias and the acceleration-sensitive bias of the dynamically tuned gyroscopes(DTGs).In order to reduce experimental cost,the D-optimal criteria with constraints are constructed.The turntable positions and the number of test points are chosen to build D-optimal experimental designs.The D-optimal experimental designs are tested by multi-position calibration experiment for tactical-grade DTGs.Test results show that,with the same cost,the fit uncertainty is reduced by about 50% by using the D-optimal 8-position experimental procedure,compared to using a defacto standard experimental procedure in ANSI/IEEE Std 813-1988.Furthermore,the new experimental procedure almost achieves optimal accuracy with only 12-position which is half the cost of the widely adopted 24-position experimental procedure for achieving optimal accuracy.     

国军标电磁兼容检测实验室间的能力比对

详细介绍了国军标电磁兼容检测实验室进行实验室间比对的方案,比对器具的选择和比对数据的处理方法,分析了国军标电磁兼容实验室比对的特点,用平均值、数据偏差等参数对国防系统实验室4个比对项目的数据进行了分析,研究实验室间测试结果存在差异的原因,并给出改进建议。     

对民航乘务英语课程的再认识

民航乘务英语课程需要区分"教"与"训"的差别。前者强调知识性内容的讲授和教学,后者强调技能性服务语言的训练和使用。民航乘务英语课程是乘务知识和服务语言技能的"合二为一"。     

美国教育资金渠道与管理体制

对美国教育资金来源渠道和管理体制加以介绍,以作者在美国见闻和感受,详细介绍了美国教育的地方管理、校区划分、融资渠道、资金使用与管理体制诸方面的真实情况,通过对美国教育资金管理的实地考察,对我国目前舆论界所关注的教育产业化问题提出了质疑。     

测试性建模与分析在显示控制单元中的应用

测试性分析与评估是测试性设计工作的重要环节,采用的方法一般有基于经验的加权法和基于模型的分析法。本文采用了基于模型的方法对显示控制单元的测试性进行了分析与评估,验证了显示控制单元的测试性设计指标是否达到要求,并对显示控制单元的测试性设计提出了改进建议。     

基于故障物理的电路板可靠性分析

在装备生命周期的各阶段,其承受的环境载荷都可能对装备造成累积损伤,进而引发故障。从装备设计特性和寿命期环境应力分布及其相互作用角度来分析装备的故障更符合其未来实际使用情况。介绍了电路板常用的故障物理模型,阐述了基于故障物理的电路板可靠性分析流程,明确了潜在故障仿真思路,为装备早期可靠性设计、测试性设计与评价提供了方法依据。     

Variable-fidelity optimization with design space reduction

Advanced engineering systems, like aircraft, are defined by tens or even hundreds of design variables. Building an accurate surrogate model for use in such high-dimensional optimization problems is a difficult task owing to the curse of dimensionality. This paper presents a new algorithm to reduce the size of a design space to a smaller region of interest allowing a more accurate surrogate model to be generated. The framework requires a set of models of different physical or numerical fidelities. The low-fidelity (LF) model provides physics-based approximation of the high-fidelity (HF) model at a fraction of the computational cost. It is also instrumental in identifying the small region of interest in the design space that encloses the high-fidelity optimum. A surrogate model is then constructed to match the low-fidelity model to the high-fidelity model in the identified region of interest. The optimization process is managed by an update strategy to prevent convergence to false optima. The algorithm is applied on mathematical problems and a two-dimen-sional aerodynamic shape optimization problem in a variable-fidelity context. Results obtained are in excellent agreement with high-fidelity results, even with lower-fidelity flow solvers, while showing up to 39% time savings.