气温的局部线性及多项式预测

利用局部线性预测法及局部多项式预测法,对气温非线性时间序列进行预测,并分析了预测误差,结果显示,局部线性预测法、局部多项式预测法对非线性时间序列具有良好的特性。     

常用预测方法应用分析

本文针对GM（1，1）的预测方法，介绍了其原息模型、新息模型和等维新息模型的建摸方法，比较分析了基于GM（1，1）的各种预测模型应用的可靠性问题。     

Space Environment Prediction for SZ-4 and SZ-5

The Space Environment Prediction Center (SEPC) of the Center for Space Science and Applied Research of the Chinese Academy of Sciences (CSSAR, CAS)took on the mission of offering the space environment parameters which may be of use to the safety of manned spacecraft. In order to complete the space environment safety guarantee mission for SZ-4 and SZ-5, SEPC improved the space environment monitoring system, database system, prediction result display system, prediction implementation system, etc. For guaranteeing the safety of the airship and cosmonaut in the first manned SZ-5, flying experiment mission,SEPC developed the software for analyzing radiation dose and early-warning software for large debris collision with SZ-5. Three months before the flights of SZ-4 and SZ-5, SEPC began to predict the safe launch period in view of the space environment, and offered timely and valid reference opinions for selecting the safety period. Especially during the mission of SZ-5, SEPC analyzed the space high-energy environment in a pre-arranged orbit and abnormal orbit andevaluated the radiation dose which cosmonauts may encounter in space. The evaluation offered an important reference for cosmonaut safety and decisionmaking in the SZ-5 mission. The calculation of the distribution of large debris and the collision risk assessment at different orbit entry times for SZ-5 provided an important base for the superior department to make flight decisions.     

Prediction of ionospheric total electron content using adaptive neural network with in-situ learning algorithm

The Ionospheric Total Electron Content is responsible for the group delay of the signals from the Navigation satellites. This delay causes ranging error, which in turn degrades the accuracy of position estimated by the receivers. For critical applications, single frequency receivers resort to Satellite Based Augmentation Systems in order to have improved accuracy and integrity. The performance of these systems in terms of accuracy can be improved if predictions of the delays are available simultaneously with real measurements. This paper attempts to predict the Total Electron Content using adaptive recurrent Neural Network at three different locations of India. These locations are selected at the magnetic equator, at the equatorial anomaly crest and outside the anomaly range, respectively. In-situ Learning Algorithm has been used for tracking the non-stationary nature of the variation. Prediction is done for different prediction intervals. It is observed that, for each case, the mean and root mean square values of prediction errors remain small enough for all practical applications. Analysis of Variance is also done on the results.     

基于灰度预测的无刷直流电机控制

针对传统PID控制器抗干扰能力差，参数调节繁琐等问题，提出了灰度预测控制器。对灰度预测算法进行了详细的理论分析和数学建模，利用最速梯度法对控制器参数进行调整，设计了参数自适应调整的控制器；对飞轮使用的无刷直流电机进行了较为准确的模型建立，并在此基础上设计了基于灰度预测控制器的电机控制仿真模型。通过仿真分析了两种控制器在正常加速和受到干扰两种情况下的不同表现，验证了灰度预测控制器在调节效果和稳定性等方面的优越性。     

航天器数据预测中的因果关系调整技术应用研究

在航天领域，预测参数不但受其自身时序变化的影响，也普遍受到关联因素的交叉影响。因果因素的影响也需要在时序预测过程中被考虑，该类问题被列入因果调整技术当中。为了更全面地反映航天器参数变化的实际情况，提出了一种基于层次分析法（AHP）的因果调整方法。该方法提供了因果因素的判断调整方法，并将调整系数应用于时序模型预测的修正。最终，建立了一个因果与时序预测有机结合的预测体系。     

Reducing variability in short term orbital lifetime prediction

Within the last year three major re-entries occurred. The satellites UARS, ROSAT and Phobos-Grunt entered Earth’s atmosphere with fragments reaching the surface. Due to a number of uncertainties in propagating an object’s trajectory the exact place and time of a satellite’s re-entry is hard to determine. Major influences when predicting the re-entry time are the changing precision of the available orbital data, the satellite’s ballistic coefficient, the activity of the sun which influences the Earth’s atmosphere and the underlying quality of the atmospheric model. In this paper a method is presented which can reduce the variability in short-term orbital lifetime prediction induced by fluctuating orbital data accuracies. A re-entry campaign is used as a reference for this purpose. For a window of a few weeks before the re-entry the position data of a synthetic object is disturbed considering different degrees of orbital data errors. As a result different predictions will exist for the generated position data of a given day. Using a regression algorithm on the available data an average position is obtained, which is then used for the orbital lifetime prediction. The effect of this measure is a more consistent prediction of the orbital lifetime. The paper concludes with the comparison of the generated re-entry windows in various test cases for the original and the averaged data.     

航天器故障诊断和预测天地一体化集成系统

在轨航天器和地面航天飞控中心天地2个系统缺乏相互支持和配合,是导致对航天器故障诊断和预测能力不足的重要因素之一。为了提高航天器故障诊断和预测的有效性、可靠性和准确性,需要将天地2个系统集成为一个整体（天地一体化系统）。设计了航天器故障天地一体化集成诊断和预测系统,讨论了航天器故障天地一体化集成诊断和预测方法,对航天器故障天地一体化集成诊断系统和方法的特点进行了分析。将天地2个系统集成在一起对航天器故障进行诊断和预测,其效率、准确性和可靠性较高。     

基于灰色理论的民航旅客运输周转量预测

对近年来民航旅客运输周转量数据进行收集整理,运用灰色预测方法,建立GM(1,1)预测模型,对未来的旅客周转量进行预测。该方法具有系统性、联系性和动态性的特点。经精度检验表明,该模型的精度等级为好。     

多处损伤的疲劳裂纹扩展分析方法研究

多处损伤（ＭＳＤ）影响老龄飞机结构完整性的重要因素之一。本文以线弹性断裂力学为基础,建立了一套工程适用且具有良好预测精度的ＭＳＤ疲劳裂纹扩展分析方法。