EDI(即Elec-tronic Date Inter-change的简称)是利用电子数据输入取代人工数据输入的一种方式,用来传送商务文件以及金融信息,进行支付等。具体地讲EDI是指标准化的商务单据或者商务文件,在一个公司的电子计算机应用系统和其贸易伙伴的...EDI(即Elec-tronic Date Inter-change的简称)是利用电子数据输入取代人工数据输入的一种方式,用来传送商务文件以及金融信息,进行支付等。具体地讲EDI是指标准化的商务单据或者商务文件,在一个公司的电子计算机应用系统和其贸易伙伴的电子计算机应用系统之间实现电子传输,EDI所传输的商务单据都是标准化的,按照事先规定的格式,里面包含必备数据和一部分备选数据,以便完成一种商务交易。EDI由三部分组成:一是一种书写的“标准”方式,即EDI标准,二是翻译能力,即EDI软件;三是一种邮寄的服务,即网络服务。EDI应用方式主要分为二种。展开更多
The dynamic responses of the arch dam including dam-foundation-storage capacity of water system,using two different earthquake input models,i.e.viscous-spring artificial boundary(AB)condition and massless foundation(M...The dynamic responses of the arch dam including dam-foundation-storage capacity of water system,using two different earthquake input models,i.e.viscous-spring artificial boundary(AB)condition and massless foundation(MF),were studied and analyzed for the 269 m high Baihetan arch dam under construction in China.By using different input models,the stress and opening of contraction joints(OCJs)of arch dam under strong shock were taken into consideration.The results show that the earthquake input models have slight influence on the responses including earthquake stresses and openings of contraction joints in different extents.展开更多
Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroe...Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroeconomic projections and in assessing macroeconomic risks. Of particular interest is the question of the extent to which the price of oil is helpful in predicting recessions. This paper presents a statistical learning method （SLM） based on combined fuzzy system （FS）, artificial neural network （ANN）, and support vector regression （SVR） to cope with optimum long-term oil price forecasting in noisy, uncertain, and complex environments. A number of quantitative factors were discovered from this model and used as the input. For verification and testing, the West Texas Intermediate （WT1） crude oil spot price is used to test the effectiveness of the proposed learning methodology. Empirical results reveal that the proposed SLM-based forecasting can model the nonlinear relationship between the input variables and price very well. Furthermore, in-sample and out-of-sample prediction performance also demonstrates that the proposed SLM model can produce more accurate prediction results than other nonlinear models.展开更多
Input selection is probably one of the most critical decision issues in neural network designing, because it has a great impact on forecasting performance. Among the many applications of artificial neural networks to ...Input selection is probably one of the most critical decision issues in neural network designing, because it has a great impact on forecasting performance. Among the many applications of artificial neural networks to finance, time series forecasting is perhaps one of the most challenging issues. Considering the features of neural networks, we propose a general approach called Autocorrelation Criterion (AC) to determine the inputs variables for a neural network. The purpose is to seek optimal lag periods, which are more predictive and less correlated. AC is a data-driven approach in that there is no prior assumptiona bout the models for time series under study. So it has extensive applications and avoids a lengthy experimentation and tinkering in input selection. We apply the approach to the determination of input variables for foreign exchange rate forecasting and conductcomparisons between AC and information-based in-sample model selection criterion. The experiment results show that AC outperforms information-based in-sample model selection criterion.展开更多
文摘EDI(即Elec-tronic Date Inter-change的简称)是利用电子数据输入取代人工数据输入的一种方式,用来传送商务文件以及金融信息,进行支付等。具体地讲EDI是指标准化的商务单据或者商务文件,在一个公司的电子计算机应用系统和其贸易伙伴的电子计算机应用系统之间实现电子传输,EDI所传输的商务单据都是标准化的,按照事先规定的格式,里面包含必备数据和一部分备选数据,以便完成一种商务交易。EDI由三部分组成:一是一种书写的“标准”方式,即EDI标准,二是翻译能力,即EDI软件;三是一种邮寄的服务,即网络服务。EDI应用方式主要分为二种。
基金Projects(51109029,51178081,51138001)supported by the National Natural Science Foundation of ChinaProject(2013CB035905)supported by the National Basic Research Program of China
文摘The dynamic responses of the arch dam including dam-foundation-storage capacity of water system,using two different earthquake input models,i.e.viscous-spring artificial boundary(AB)condition and massless foundation(MF),were studied and analyzed for the 269 m high Baihetan arch dam under construction in China.By using different input models,the stress and opening of contraction joints(OCJs)of arch dam under strong shock were taken into consideration.The results show that the earthquake input models have slight influence on the responses including earthquake stresses and openings of contraction joints in different extents.
文摘Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroeconomic projections and in assessing macroeconomic risks. Of particular interest is the question of the extent to which the price of oil is helpful in predicting recessions. This paper presents a statistical learning method （SLM） based on combined fuzzy system （FS）, artificial neural network （ANN）, and support vector regression （SVR） to cope with optimum long-term oil price forecasting in noisy, uncertain, and complex environments. A number of quantitative factors were discovered from this model and used as the input. For verification and testing, the West Texas Intermediate （WT1） crude oil spot price is used to test the effectiveness of the proposed learning methodology. Empirical results reveal that the proposed SLM-based forecasting can model the nonlinear relationship between the input variables and price very well. Furthermore, in-sample and out-of-sample prediction performance also demonstrates that the proposed SLM model can produce more accurate prediction results than other nonlinear models.
基金This research is partially supported by Chinese Academy of SciencesNational Science Foundation of ChinaJapan Society for the Promotion of Science.
文摘Input selection is probably one of the most critical decision issues in neural network designing, because it has a great impact on forecasting performance. Among the many applications of artificial neural networks to finance, time series forecasting is perhaps one of the most challenging issues. Considering the features of neural networks, we propose a general approach called Autocorrelation Criterion (AC) to determine the inputs variables for a neural network. The purpose is to seek optimal lag periods, which are more predictive and less correlated. AC is a data-driven approach in that there is no prior assumptiona bout the models for time series under study. So it has extensive applications and avoids a lengthy experimentation and tinkering in input selection. We apply the approach to the determination of input variables for foreign exchange rate forecasting and conductcomparisons between AC and information-based in-sample model selection criterion. The experiment results show that AC outperforms information-based in-sample model selection criterion.
