SFEP文本因果关系提取及其与SFN转化研究

为将系统故障演化过程(system fault evolution process，SFEP)的文本描述转化为空间故障网络(space fault network，SFN)结构，用于故障分析，本文提出SFEP文本因果关系提取方法，及其与SFN基本结构的转化方法。首先给出SFEP中事件的几种典型因果关系。随后提出因果关系与SFN基本结构的转化流程。本文方法围绕着关键字和因果关系组模式展开，通过模型的不断学习补充和丰富关键字和组模式。最终使方法具备将SFEP文本转化为SFN结构的能力。以飞机起落架故障发生过程文本为例进行了应用，实验结果表明该方法可用于SFEP文本中的因果关系分析，并得到了理想的SFN。完善的关键字和组模式有利于使用计算机智能处理SFEP的SFN。     

Nonlinear correlation between RMB internationalization and nonferrous metal prices

The correlation between Renminbi (RMB) internationalization and nonferrous metal prices was studied using the nonlinear Granger causality test and the dynamic conditional correlation-generalized autoregressive conditional heteroskedastic (DCC-GARCH) model. The results indicate that the relationship between RMB internationalization and nonferrous metal prices reflects a complex nonlinear mechanism. There was no mutual influence between RMB internationalization and nonferrous metal prices prior to the trials of the RMB settlement in the cross-border trade in July 2009. Since then, however, a bidirectional causal relationship between RMB internationalization and the price of copper and a unidirectional causal relationship from the price of aluminum to RMB internationalization were examined. In addition, due to the impact of extreme events, such as economic and financial crises, RMB internationalization and nonferrous metal prices are not always positively correlated but are rather occasionally negatively correlated.     

Functional Causality between Oil Prices and GDP Based on Big Data

This paper examines the causal relationship between oil prices and the Gross Domestic Product (GDP) in the Kingdom of Saudi Arabia. The study is carried out by a data set collected quarterly, by Saudi Arabian Monetary Authority, over a period from 1974 to 2016. We seek how a change in real crude oil price affects the GDP of KSA. Based on a new technique, we treat this data in its continuous path. Precisely, we analyze the causality between these two variables, i.e., oil prices and GDP, by using their yearly curves observed in the four quarters of each year. We discuss the causality in the sense of Granger, which requires the stationarity of the data. Thus, in the first Step, we test the stationarity by using the Monte Carlo test of a functional time series stationarity. Our main goal is treated in the second step, where we use the functional causality idea to model the co-variability between these variables. We show that the two series are not integrated; there is one causality between these two variables. All the statistical analyzes were performed using R software.     

基于空间合作关系的基站流量预测模型

针对传统的自回归积分移动平均（ARIMA）模型和长短时记忆（LSTM）单元在基站流量预测中没有利用基站（BS）间合作关系的问题，提出一种利用由用户群体在不同基站下访问产生的基站合作关系的流量预测（TPBC）算法。首先，通过基站之间的合作关系构建基站合作网络，并对此合作网络进行社区划分得到基站社区；然后，通过格兰杰因果关系检验方法寻找与目标基站同一社区且关系最紧密的若干基站，作为目标基站的合作基站；最后，使用LSTM和词嵌入层（Embedding）搭建混合神经网络，并根据目标基站和合作基站的流量信息进行流量预测。实验结果表明，TPBC在基站流量预测上的均方根误差（RMSE）相比ARIMA和LSTM分别减小了29.19%和27.47%。TPBC能有效提高基站流量预测准确率，在流量卸载和绿色节能等领域具有重要意义。     

The short- and long-run efficiency of energy,precious metals,and base metals markets: Evidence from the exponential smooth transition autoregressive models

The aim of this paper is to investigate the long and short-run relationship between spot and futures prices of the energy, precious metals, and base metals markets. We analyze daily data from January 1985 to February 2019. The empirical findings based on the cointegration test, which follows a nonlinear process, suggest that the spot prices of energy and metals assets have long-run relationships with their futures prices. Nonparametric Granger causality test results also indicate bi-directional causality among futures and spot prices. These findings indicate that the energy and metals markets are informationally efficient in the sense of Fama (1970).     

资源型城市旅游业与经济增长互动关系实证研究——以焦作市为例

以焦作市为例，利用2000-2015年焦作市旅游业发展和经济增长的相关时间序列数据，通过协整检验、Granger因果关系检验和误差修正模型来研究资源型城市旅游业发展和经济增长之间的互动关系。结果显示，资源型城市旅游业的发展和经济增长存在很强的正相关关系，具有长期稳定的均衡关系，并且二者具有双向的Granger因果关系：旅游业的发展有助于促进资源型城市地区经济的增长，经济的增长反过来又会带动旅游业的发展。在此结论的基础上提出资源型城市发展旅游业的相关政策建议。      

要求之外——一次高层办公楼设计竞标随感

在某高层办公建筑的设计过程中,主动地挖掘项目内在的要求与特征,提出超越纯外观要求的界限。通过对城市脉络、基地状态、功能判断等一直到内在要求方面的因果关系的梳理,逐渐明晰了设计的需要,使设计更具说服力与理性精神。     

改进BP神经网络及其在西北建筑业预测中的应用

BP神经网络是分析处理复杂非线性问题的一种有效方法,是目前广泛应用的一种神经网络,已被逐渐应用于对宏观经济问题的研究中。本文有机地整合了计量经济学与BP神经网络,建立了基于因果关系理论来确定BP网络的输入变量,基于协整理论来分析BP网络系统的可靠性,基于学习率可变的动量BP算法的用于研究经济领域问题的改进BP神经网络预测模型,加强了网络模型的理论基础,提高了网络模型的质量,并将其应用于西北建筑业的预测和控制中,取得了令人满意的效果。     

Improved CCM for variable causality detection in complex systems

Convergent cross-mapping (CCM), has been largely implemented for variable causality detection in complex systems like chemical process. However, this method is susceptible to problems regarding parameter selection and threshold determination. The synchronization phenomenon and the Moran effect, which are two interference terms in causality detection, must also be addressed. Therefore, an improved CCM is proposed to overcome these limitations in this paper. In the improved CCM, the optimal embedding dimension is selected based on the pseudo-nearest-neighbor theory. Also, Monte Carlo simulation is adopted to evaluate the convergence threshold. Next, by using the defined time delay detection function, the synchronization phenomenon and the Moran effect are identified to reduce the interference terms and further improve the accuracy. Finally, the improved CCM method is applied in a numerical example and a hydrocracking process to demonstrate its feasibility and superior performance than other methods.     

基于GDP-电能消费耦合关系的中长期电量预测

建立了一种基于用电量和GDP之间耦合关系的中长期电量预测模型。首先利用协整检验和格兰杰（Granger）因果检验，剖析电能消费和经济发展之间的协整关系和因果关系，并建立中长期电量预测模型。然后采用误差修正方法对预测模型进行短期调节，以提高模型的鲁棒性以及预测精度。以某地区1991—2015年的用电量和GDP数据作为算例输入数据，结果表明：通过构建电能消费和经济发展之间的耦合关系，有助于提高预测模型的解释能力，同时含短期调节的中长期用电量预测模型具有更高的预测精度。