航班计划优化研究概述

从航班计划优化的不同时间阶段分析,可以将航班计划优化分为航班计划静态编排优化、基于航班延误预测的航班计划动态反馈优化和基于机场协同决策(A-CDM)的航班计划动态调整角度三类;进而从航班时刻、机型指派、航班频率等编制环节分析了航班计划静态编排优化;随后利用延误波及预测与数据挖掘预测的优化方法分析了基于航班延误预测的航班计划动态反馈优化的相关研究。最后,根据航班计划优化复杂性分析,给出了航班计划优化的发展趋势和未来研究方向。     

Time preference and international trade

We first consider a closed model, where households' time discount depends on externality in consumption. We can prove that there is a unique steady state, which is a saddle point. Then we extend the model to a two‐country world, and derive the condition on the effects of consumption externality under which there is a unique free trade steady state with saddle‐point stability.     

基于GM(1,1)模型的造纸业上市公司财务研究——以冠豪高新为例

财务风险是企业调整发展战略、提升管理水平的重要参考指标之一。财务风险预测模型的建立能够预测企业在中短期内的财务风险,为企业敲响警钟。以造纸业上市公司冠豪高新为例,选取近五年财务杠杆系数为风险指标,建立GM(1,1)风险预测模型,结果显示该公司短期内财务风险呈下降趋势,调查发现这主要得益于产品成本的降低以及营销策略的改变。     

Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting

Wind power forecasts with lead times of up to a few hours are essential to the optimal and economical operation of power systems and markets. Vector autoregression (VAR) is a framework that has been shown to be well suited to predicting for several wind farms simultaneously by considering the spatio-temporal dependencies in their time series. Lasso penalisation yields sparse models and can avoid overfitting the large numbers of coefficients in higher dimensional settings. However, estimation in VAR models usually does not account for changes in the spatio-temporal wind power dynamics that are related to factors such as seasons or wind farm setup changes, for example. This paper tackles this problem by proposing a time-adaptive lasso estimator and an efficient coordinate descent algorithm for updating the VAR model parameters recursively online. The approach shows good abilities to track changes in the multivariate time series dynamics on simulated data. Furthermore, in two case studies it shows clearly better predictive performances than the non-adaptive lasso VAR and univariate autoregression.     

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.     

基于SARIMA-SVR组合模型的 空气质量指数预测

空气质量指数(AQI)在波动中既具有整体的时间序列线性特征和明显的季节性波动周期,又具有多种因素影响的不确定性,为了提高AQI的预测精度,基于Ri386 3.3.3和Matlab R2014a两种编程软件,提出了一种同时具有线性和非线性的复合特征的时间序列预测模型——SARIMA-SVR组合模型。以太原市2014年1月—2019年7月的AQI月均值数据为基础,利用SARIMA时间序列模型进行线性预测,利用SVR模型对残差进行非线性预测,加和得到组合预测模型的预测结果,分析比较SARIMA,SVR和SARIMA-SVR这3种模型的预测结果和平均绝对百分比误差。结果表明,组合预测模型发挥了2种模型各自的优势,相较于单一预测模型的预测结果而言,其预测精度更高,稳定性更好。通过此模型得到的空气质量预测结果不仅可为人们的日常生活提供指导,而且可为大气污染的防治工作提供科学依据和借鉴意义。     

Non-linear Gaussian sovereign CDS pricing models

Prior literature indicates that quadratic models and the Black–Karasinski model are very promising for CDS pricing. This paper extends these models and the Black [J. Finance 1995, 50, 1371–1376] model for pricing sovereign CDS’s. For all 10 sovereigns in the sample quadratic models best fit CDS spreads in-sample, and a four factor quadratic model can account for the joint effects on CDS spreads of default risk, default loss risk and liquidity risk with no restriction to factors correlation. Liquidity risk appears to affect sovereign CDS spreads. However, quadratic models tend to over-fit some CDS maturities at the expense of other maturities, while the BK model is particularly immune from this tendency. The Black model seems preferable because its out-of-sample performance in the time series dimension is the best.     

Time and frequency domain causality Testing: The causal linkage between FDI and economic risk for the case of Turkey

This study aims to explore the causal relationship between economic risk and foreign direct investment (FDI) inflows for the case of Turkey. With the aim of establishing robust findings for the research in mind, both traditional and modern causality techniques are utilized; time domain Granger (1969, “Investigating Causal Relations by Econometric Models and Cross-Spectral Methods.” Econometrica 37: 424–438.), Toda and Yamamoto (1995, “Statistical Inference in Vector Autoregressions with Possibly Integrated Processes.” Journal of Econometrics 66 (1–2): 225–250.), Fourier Toda-Yamamoto and frequency domain Breitung and Candelon (2006, “Testing for short- and long-run causality: A frequency-domain approach.” Journal of Econometrics 132 (2): 363–378.) spectral causality test. Our empirical findings reveal that; economic risk changes in Turkey significantly lead to changes in FDI inflows. However, there is no evidence of causality running from FDI to economic risk. The findings imply that economic risk is an essential determinant of FDI inflows in Turkey. Our findings are compatible with historical macroeconomic developments in Turkey and imply important policy implications. The results of this study can be generalized for other emerging economies that have similar macroeconomic environments, in order to create useful policy implications regarding FDI inflow.     

WHAT DETERMINES VACATION LEAVE? THE ROLE OF GENDER

Vacation leave is introduced in workplaces to improve the working environment. Surprisingly, it has been observed that a large number of workers do not use all of their entitled vacation days. This paper provides a novel set of facts about the gender differences in taking vacation time using the Canadian Workplace Employee Survey, which is a linked longitudinal employer‐employee dataset. The results show considerable differences between men and women in the estimated effects of some demographic characteristics after controlling for job and workplace characteristics. However, they reveal significant implications of work arrangements (e.g., part‐time work, flexible work schedules, and home‐based work), job promotion, supervisory tasks, and union membership for vacation use, for both men and women. This paper provides further insights on the use of fringe benefits that may be useful to policymakers and businesses.     

《摆脱贫困》中蕴含的精准扶贫理念——习近平精准扶贫理念在福建孕育及实践

习近平扶贫理念随着时代发展而完善,从“摆脱贫困”到“精准扶贫”再到“精准脱贫”,其理念一脉相承,其思想内涵与时俱进,不断拓展深化,形成了从理念到理论再到实践的“知行合一”理论实践体系。习近平在福建任职期间进行了“摆脱贫困”理论及实践探索,提出了许多富有创造性的扶贫脱贫观点,如“扶贫先扶志、念好山海经、科技兴农、建设农村党组织、四下基层、滴水穿石”等,明确了“扶持谁一谁来扶一怎么扶”的扶贫脱贫思路,在精神扶贫、扶贫策略、扶贫路径、扶贫组织保障、多元扶贫力量、脱贫内生动力、脱贫长效机制等方面蕴含着精准扶贫精准脱贫理念。