一种航班计划过航路点时间数据修正及实际过点时间实时计算方法的研究

随着航空运输业的快速发展,航班计划过航路点时间和实际过航路点时间数据的重要性日益凸显。本文针对当前航班计划信息数据中存在部分航班连续多个航路点计划过点时间重合,航班实际过点时间更新不及时或采集不到等问题,提出了相应的解决策略。采用历史飞行数据预估法,解决航路点计划过点时间重合的问题;使用雷达航迹数据,通过算法模型实时计算航班实际过点时间的问题。最后,通过实验数据,展示了修正后航班计划过点时间,相邻航路点时间间隔的准确性和实时计算过点时间较高准确率的成果。

基于LSTM的航班过点时间预测

为了提高空管流量管理效率,在飞行计划阶段,精确推测航空器预计过点时间,提出了基于长短时记忆网络(Long Short-Term Memory,LSTM)的航班过点时间预测方法。通过关联航班飞行计划与实际雷达数据,根据计划数据航路点与实际过点时间信息构建了预测模型。将模型预测结果与真实航班过点时间进行对比,将预测过点时间与实际过点时间的绝对值误差作为评价标准,结果表明,基于LSTM的航班过点时间预测模型误差更小,以国内航班CCA4439为例,LSTM模型精度更高,可以将航班的过点时间误差控制在30s以内。

基于密度聚类与匹配算法的异常飞行行为挖掘

在空中交通愈加拥挤的背景下,航空器的异常飞行行为的有效挖掘可以辅助管制员进行调配决策。现有方法只能辨识飞机空间位置特征异常,存在水平可扩展性的局限。本文考虑位置、速度、高度和航向4个异常特征,采用高度层划分策略、局部异常因子和快速覆盖树对基于密度的有噪声应用中的空间聚类(Density-based spatial clustering of applications with noise,DBSCAN)方法进行改进,提出局部异常因子改进的考虑速度、方向及高度的基于密度聚类方法(Density-based spatial clustering considering speed,direction and high level improved by local outlier factor,LOFDBSC-SDH)密度聚类算法对正常航迹模式进行快速准确提取。然后,基于正常航迹模式设计考虑过点时间和上述异常特征的航迹匹配算法,挖掘异常飞行行为。最后,通过实验仿真验证了本文方法的有效性和应用价值。

不确定性影响下航班进场管理多策略比较研究

创建了基于过点时间和基于分时段尾随间隔限制的进场管理模型,并设计人工智能算法对模型进行求解,并结合实际进场运行中的尾随间隔限制策略,采用蒙特卡洛仿真方法对受到不确定性影响下三种策略的实施效果进行了比较。仿真结果表明,确定性情况下,过点时间管理策略在终端区内外的总延误小于全时段及分时段尾随间隔限制策略,效果更优。当受不确定性影响时,基于时间的管理策略下航班总延误的增加程度以及航班顺序出现反序的情况都更明显,尾随间隔限制策略更具鲁棒性。

A Novel Method for Banks to Monitor the Cumulative Loss Due to Defaults

Banking institutions all over the world face significant challenge due to the cumulative loss due to defaults of borrowers of different types of loans. The cumulative default loss built up over a period of time could wipe out the capital cushion of the banks. The aim of this paper is to help the banks to forecast the cumulative loss and its volatility. Defaulting amounts are random and defaults occur at random instants of time. A non Markovian time dependent random point process is used to model the cumulative loss. The expected loss and volatility are evaluated analytically. They are functions of probability of default, probability of loss amount, recovery rate and time. Probability of default being the important contributor is evaluated using Hidden Markov modeling. Numerical results obtained validate the model.

Insights into the Temporal Gene Expression Pattern in Lymantria dispar Larvae During the Baculovirus Induced Hyperactive Stage

Baculoviruses are effective biological control agents for many insect pests. They not only efficiently challenge the host immune system but also make them hyperactive for better virus dispersal. Some investigations have focused on the viral mechanisms for induction of such altered response from the host. However, there are no current studies monitoring changes in gene expression during this altered phenotype in infected larvae. The L. dispar multiple nucleopolyhedrovirus(Ld MNPV) induces hyperactivity in third instar L. dispar larvae at 3-days post infection(dpi), to continued till 6 dpi. The transcriptome profiles of the infected and uninfected larvae at these time points were analyzed to provide new clues on the response of the larvae towards infection during hyperactivity. Gene ontology enrichment analysis revealed, most of the differentially expressed genes(DEGs) were involved in proteolysis, extracellular region, and serine-type endopeptidase activity. Similarly, Kyoto Encyclopedia of Genes and Genome enrichment analysis showed maximum enrichment of 487 genes of the signal transduction category and neuroactive ligand–receptor interaction sub-category with 85 annotated genes. In addition, enrichment map visualization of gene set enrichment analysis showed the coordinated response of neuroactive ligand–receptor interaction genes with other functional gene sets, as an important signal transduction mechanism during the hyperactive stage. Interestingly all the DEGs in neuroactive ligand–receptor interactions were serine proteases, their differential expression during the hyperactive stage correlated with their conceivable involvement in disease progression and the resulting altered phenotype during this period. The outcome provides a basic understanding of L. dispar larval responses to Ld MNPV infection during the hyperactive stage and helps to determine the important host factors involved in this process.

Determinants of lexical access in pure-anomic recovery:a longitudinal study

Many studies involving lexical access in picture-naming tasks have been undertaken at a point in time,mainly focusing on age of acquisition(AoA).To identify the real determinates of lexical access in recovery and their traces in the brain,we carried out a longitudinal study on a Chinese pure anomic patient using multiple logistic regression analysis.We found that AoA played an important role in early recovery but not in total recovery,whereas familiarity was significant in the whole process.From a new dynamic point of view,our results indicate that AoA and familiarity are the main determinants of lexical access in anomia recovery.We suggest that the changing effects of AoA during recovery may be related to the pathologic process;AoA and familiarity should be taken into account in constructing materials to assess and treat anomic patients.

A reduced combustion kinetic model for the methanol-gasoline blended fuels on SI engines.

A reduced combustion kinetic model for the methanol-gasoline blended fuels for SI engines was developed. Sensitivity analysis and rate constant variation methods were used to optimize the kinetic model. Flame propagation, shock-tube and jet-stirred reactor systems were modeled in CHEMKIN. The laminar flame speed, ignition delay time and change in concentrations of species were simulated using the reduced kinetic model. The simulation results of reduced chemical mechanism agreed well with the relevant experimental data published in the literature. The experimental investigations on engine bench were also carried out. The in-cylinder pressure and exhaust emissions were obtained by using a combustion analyzer and an FTIR(Fourier transform infrared spectroscopy) spectrometer. Meanwhile, an engine in-cylinder CFD model was established in AVL FIRE and was coupled with the proposed reduced chemical mechanism to simulate the combustion process of methanol-gasoline blends. The simulated combustion process showed good agreement with the engine experimental results and the predicted emissions were found to be in accordance with the FTIR results.