利用人工神经网络提前1h预报电离层TEC

提出了一种利用人工神经网络提前1h预报电离层TEC的简便方法. 考虑到实际工程应用要求, 没有使用其他空间天气参数, 而是选择电离层TEC观测数据本身作为输入参数. 输入参数为当前时刻TEC、一阶差分、相对差分和时间, 输出参数为预报时刻TEC. 利用文中介绍的GPS/TEC处理方法解算厦门站2004年电离层TEC观测数据, 对预报方法进行评估, 全年平均相对误差为9.3744%, 预报结果与观测值相关性达到了0.96678. 结果表明, 利用人工神经网络方法提前1h预报电离层TEC有很好的应用前景.      

半球谐振陀螺仪寿命的一种长周期预测方法

为了缩短半球谐振陀螺仪寿命实验周期,降低实验成本,提出了一种针对漂移数据的残差修正ARGM(1,1)(Autoregressive GM(1,1))寿命预测方法。该方法利用神经网络与支持向量机中的自回归方式改进灰色模型,提高了模型的自适应能力,增强了模型的学习能力与预测能力,降低了模型回归学习的时间消耗和数据量要求,提高了预测效率。采用小波包络分析预处理某型号半球谐振陀螺仪的漂移数据,利用提出的预测方法对处理后的数据进行长周期预测,并结合灰色关联分析方法,分析失效阶段并最终预测出半球谐振陀螺仪的寿命。实验表明,残差修正ARGM(1,1)模型对半球谐振陀螺仪漂移数据的长期预测精度高于传统GM(1,1)模型、BP神经网络与支持向量机,结果也表明了研究方法的正确性和有效性。     

基于可靠性增长预测模型的航空发动机可靠性评估

通过可靠性增长预测模型充分利用定型前内场台架试验及外场试飞提供的大量数据对技术状态不断变化的发动机进行可靠性评估,并与经典的累计平均故障间隔时间(MTBF)估算值作了比较,结果表明:传统的累计MTBF评估方法没有考虑研制过程中技术状态的不断变化和可靠性不断增长的情况,故评估的可靠性值不符合实际情况;而可靠性增长预测模型合理、有效、实用.      

动态测试实时误差的灰色预测及其精度估计

将灰色预测应用于可重复动态测试过程,根据可重复动态测试的特点,采用统计方法有效地减小随机误差的影响,用其平均值建立预测模型,并对产生预测误差的各种因素加以分析,采用统计所得的各点方差值建立预测值精度的估计模型。实例证明,误差预测模型及精度估计模型都具有较好的效果。     

基于灰色模型的军机两级维修人力效益预测

维修人力费用估算是军用飞机寿命周期费用估算的重要组成部分。将三级维修体制简化为两级维修,可节省维修人力,并提高战备完好性。引入灰色系统Verhulst模型理论,建立了转换维修体制后的人力节省预测模型,以美空军实际节省的人力数据为例进行预测,结果表明,模型的可信性较高。     

构建航空气象和用户一体化实训平台的设想

本文结合多年对航空气象专业及飞行管制等用户的培训经验,提出了培训平台搭建的思路,进行了平台框架设计,并对今后实用训练模块进行了策划研究,为平台培训软件开发提供了理论参考。     

灰色系统理论在年用电量预测中的应用

年用电量系统具有灰色系统的特征,因此,可以用灰色系统模型对年用电量进行预测.运用灰色模型(GM(1,1))对年用电量做出预测,并与传统方法进行比较,结果证明GM(1,1)模型优于传统方法,是一种有效的预测年用电量的模型。     

A geomagnetic activity forecast for improving the efficiency of aeromagnetic surveys in Greenland

In recent years several aeromagnetic surveys were carried out in Greenland and more will be carried out in the future. We describe some of the characteristics pertinent to surveys in Greenland and the problems faced and experiences made by the survey teams working there, with special emphasis on the west coast where most surveys were conducted. Both unfavorable terrestrial weather and space weather appear to complicate survey planning. We discuss possible options available to the survey teams for mitigating the adverse effect of part of the problems, namely survey data contamination by intense geomagnetic activity. The implementation of a prototype geomagnetic activity forecast service as an aid to planning survey flights is discussed in more detail. The forecast service was tested by an independent observer, and the performance of the scheme is evaluated by a subsequent comparison between forecast and actual measurements. The comparison rendered largely acceptable results, but their validity is limited by the fact that the two-month test interval was characterized by a mostly relatively quiet magnetic field.     

Forecast of recurrent geomagnetic storms

Long-term forecast of space weather allows in achieving a longer lead time for taking the necessary precautions against disturbances. Hence, there is a need for long-term forecasting of space weather. We studied the possibility for a long-term forecast of recurrent geomagnetic storms. Geomagnetic storms recur with an approximate 27-day period during the declining phase of a solar cycle. These disturbances are caused by the passage of corotating interaction regions, which are formed by interactions between the background slow-speed solar wind and high-speed solar wind streams from a coronal hole. In this study, we report on the performance of 27-day-ahead forecasts of the recurrent geomagnetic disturbances using Kp index. The methods of the forecasts are on the basis of persistence, autoregressive model, and categorical forecast using occurrence probability. The forecasts show better performance during the declining phase of a solar cycle than other phases. The categorical forecast shows the probability of detection (POD) more than 0.5 during the declining phase. Transition of the performance occurs sharply among the declining phases and other phases.     

一类非平稳随机过程未来变化趋势的多步实时预报

本文在回避建立过程加速度模型这一传统方法的前提下，提出了一类非平衡随机过程未来变化趋势的多步实时预报模型，并对高斯白噪声背景下过程变化的共性进行了研究。文中给出了算例与仿真计算结果。