基于模糊聚类的不同机型分类方法研究

随着航空业飞速发展,飞机的种类越来越多,如何对不同机型进行归类,使飞机的设计、制造、使用、维护、保障等工作变得更加高效,是制造商和运营商亟待解决的问题。文中把飞机设计性能特征指标加以解析化和数量化,给出了模糊聚类分析对不同机型的分类计算方法,并实例分析,得到了不同机型的在不同水平下的相似关系。从而为不同机型的归类、相似机型的选择提供了一种方法,也可以作为飞机设计、营运信息、备件设施共享的依据,该方法可以综合机型多种特征,增强了不同机型分类的精确性、客观性和合理性。     

机场竞争力评价指标体系的构建

本文首先分析总结了机场竞争力的形成机理,在此基础上提出了机场竞争力的评价原则,最后,构建了一套包含4个一级指标、16个二级指标和41个三级指标的机场竞争力评价指标体系,旨在通过这套评价体系对机场的竞争力发展水平进行评估,找出机场竞争力发展过程中的优势不足,为机场在市场竞争中提高竞争力水平和核心竞争力提供科学的参考依据.     

基于遗传算法的飞机经济爬升速度优化方法

为提高宽体飞机的爬升经济性,首先建立了爬升阶段飞行动力学模型和优化目标计算模型,确定了基于速度优化的最佳爬升策略;然后,在最佳爬升策略的基础上,建立了基于遗传算法的双表速爬升优化模型,得到近似最佳爬升策略,并分析了该爬升策略的可行性;最后,以某宽体飞机为例,分析了近似最佳爬升策略的影响因素。研究结果表明:最佳爬升策略相对传统爬升策略经济性提升3%~8%,且改进后的近似爬升策略与最佳爬升策略误差不超过1.4%;飞机重量、温度偏差和成本指数均会影响爬升策略的性能参数。     

航空CFD软件可信度评价指标体系研究进展

按照CFD软件模拟的流速范围、流动特征对CFD软件的可信属性进行划分,形成亚、跨、超、高超流动模拟指标以及所对应的流动特性模拟能力指标,得到CFD软件可信度评价指标;并结合所对应的指标设计出基准级、部件级和系统级三级度量元,制定出CFD软件可信度评价准则和评价方法,建立起一套可用于评价航空CFD软件可信度的评价流程和评价体系。     

卫星测控直扩信号安全性能评价体系研究

为了定量评估直扩信号的安全性能,在给出卫星测控直扩信号安全防护定义的基础上,对卫星测控直扩信号安全性能评价指标进行了研究.在深入分析直扩信号典型威胁的基础上,提出了等效码长、调制指数、码速率截获因数、等效码长截获因数、码序列截获因数、干扰因数等衍生指标,分析、仿真了它们的影响因素,得到了它们与基本指标的关系,初步建立了直扩信号安全性能评价体系,为后续安全性能评估打下基础.     

北斗卫星导航系统测量误差指标体系

围绕北斗卫星导航系统中的伪距测量误差，全面分析系统的测量原理，提出系统误差指标体系的构建流程，构建基于误差层次分解方法的北斗卫星导航系统测量误差指标体系，指标体系由1个系统层指标、3个准则层指标、11个要素层指标和36个基础指标等51个指标组成。同时，结合实例，从卫星下行链路的绝对时延的测试需求，引出了绝对时延的测试问题，定义星载导航任务处理单元对外1PPS信号的输出口作为卫星的时间零点，给出需要测试的绝对时延的路径组成。根据目前系统的实际情况，通过每一部分的测试误差，求出整个绝对时延的测量误差精度。     

工作绩效综合评价与分级管理及实证

本文针对目前员工绩效评价中的问题进行研究。建立了绩效评价指标体系，给出工作绩效考评法；并据综合绩效进行归类分级，提出对员工分类激励的方法，给出实证结果。     

国债指数GARCH模型实证研究

上证国债指数2003年2月24日至2005年7月14日日收盘时间序列经一阶差分后是平稳序列,利用一阶差分序列建立的ARIMA模型存在自回归条件异方差,在ARIMA模型基础上建立的GARCH(1,1)模型、ARCH(1,1)-M模型、TA．RCH(1,1)模型,模型系数检验、标准化残差检验及自回归条件异方差检验都非常理想。由于一阶差分代表收益,利用GARCH(1,1)模型可以对上证国债指数日收益的波动性以及波动性的不对称性,即均值和方差进行准确地预测,同时按差分的定义可将GARcH(1,1)模型转化为预测下一交易日收盘的预测模型。     

Forecasting the geomagnetic activity of the Dst index using multiscale radial basis function networks

The Dst index is a key parameter which characterises the disturbance of the geomagnetic field in magnetic storms. Modelling of the Dst index is thus very important for the analysis of the geomagnetic field. A data-based modelling approach, aimed at obtaining efficient models from limited input–output observational data, provides a powerful tool for analysing and forecasting geomagnetic activities including the prediction of the Dst index. In this study, the process of the Dst index is treated to be a structure-unknown system, where the solar wind parameter (VBs) and the solar wind dynamic pressure (P) are the system inputs, and the Dst index is the system output. A novel multiscale RBF (MSRBF) network is introduced to represent such a two-input and single-output system, where the Dst index is related to the solar wind parameter and the dynamic pressure, via a hybrid network model consisting of two submodels: a linear part that reflects the linear relationship between the output and the inputs, and a nonlinear part that captures the effect of the interacting contribution of past observations of the inputs and the output, on the current output. The proposed MSRBF network can easily be converted into a linear-in-the-parameters form and the training of the linear network model can easily be implemented using a forward orthogonal regression (FOR) algorithm. One advantage of the new MSRBF network, compared with traditional single scale RBF networks, is that the new network is more flexible for describing complex nonlinear dynamical systems.     

Results of analysis of human impact on environment using the time series of vegetation satellite images around large industrial centers

The paper shows the efficiency of an application of the vegetation index image time series to determine long-term vegetation dynamics. The influence of large industrial centers of Siberia on the near-by vegetation is demonstrated. The analysis of the data shows that the influence of industrial waste is stronger in the Siberian North. These regions are characterized by critical conditions for vegetation existence. In the south of the Krasnoyarsk region, human impact is also important, but the possibility of vegetation self-rehabilitation is higher. The present-day economic situation in Russia is unique, with a temporary abrupt fall of industrial production and its following increase. Thus, we managed to analyze the degree of human impact on the environment within a relatively short-time interval.