Based on the changing law of municipal water demand,a trigonometric function model for short-term water demand forecast is established using the time-series analysis approach.The method for forecasting water demand du...Based on the changing law of municipal water demand,a trigonometric function model for short-term water demand forecast is established using the time-series analysis approach.The method for forecasting water demand during holidays and under unexpected events is also presented.Meanwhile,a computer software is developed.Through actual application,this method performs well and has high accuracy,so it can be applied to the daily operation of a water distribution system and lay a foundation for on-line optimal operation.展开更多
Recently, much dispute has occurred about the validity of the New Keynesian model from both theoretical and empirical views. However, a few studies have analyzed this model from the empirical perspective. Few other st...Recently, much dispute has occurred about the validity of the New Keynesian model from both theoretical and empirical views. However, a few studies have analyzed this model from the empirical perspective. Few other studies have analyzed this model directly or nearly directly. This article empirically examines the New Keynesian model focusing on inflation forecast. Generalized method of moments (GMM) is used to examine whether the typical Keynesian model with Taylor rule is empirically appropriate for the US, UK, Euro area, and Japan. The results showed: (1) the New Keynesian model fits well in most cases and explains the real economy well. Taylor rule also fits well for most cases; (2) Rational expectations for inflation rates may not be useful based on this model When AR (1) (time series analysis) model is used to capture inflation expectations instead of one-time ahead real values, the model fits well. With measured expectations, the relative weight of the forward-looking terms increase on the cost of lagged inflation and output terms, even up to the point at which the lagged inflation terms are no longer needed to rescue the new Keynesian model; and (3) Forward-looking variables play more important roles than backward-looking ones in economic activity. Results with expectations with forward-looking terms perform better in general. This New Keynesian model may reduce the importance of lagged output in some cases展开更多
Forecasting exchange rate is undoubtedly an attractive and challenging issue that has been of interest in different domains for many years. The singular spectrum analysis (SSA) technique has been used as a promising...Forecasting exchange rate is undoubtedly an attractive and challenging issue that has been of interest in different domains for many years. The singular spectrum analysis (SSA) technique has been used as a promising technique for time series forecasting including exchange rate series. The SSA technique is based upon two main choices: Window length, L, and the number of singular values, r. These values are very important for the reconstruction stage and forecasting purposes. Here the authors consider an optimum version of the SSA technique for forecasting exchange rates. The forecasting performances of the SSA technique for one-step-ahead forecast of six exchange rate series are used to find the best L and r.展开更多
This paper describes the methodology of singular spectrum analysis (SSA) and demonstratethat it is a powerful method of time series analysis and forecasting,particulary for economic time series.The authors consider th...This paper describes the methodology of singular spectrum analysis (SSA) and demonstratethat it is a powerful method of time series analysis and forecasting,particulary for economic time series.The authors consider the application of SSA to the analysis and forecasting of the Iranian nationalaccounts data as provided by the Central Bank of the Islamic Republic of Iran.展开更多
The advantage of artificial neural network and wavelet analysis are integrated through replacing the traditional S-shaped activation function with the wavelet function. One method of chaotic prediction based on wavele...The advantage of artificial neural network and wavelet analysis are integrated through replacing the traditional S-shaped activation function with the wavelet function. One method of chaotic prediction based on wavelet BP network was put forward based on the reconstruction of state space. Training data construction and networks structure are determined by chaotic phase space, and nonlinear relationship of phase points was established by BP neural networks. As an example, the new method was applied on short term forecasting of monthly precipitation time series of Sanjiang Plain with chaotic characteristics. The results showed so higher precision of the method had that the theoretical evidence would be provided for applying the chaos theory to study the variable law of monthly precipitation.展开更多
基金Natural Science Foundation of China!(No.598780 30 )
文摘Based on the changing law of municipal water demand,a trigonometric function model for short-term water demand forecast is established using the time-series analysis approach.The method for forecasting water demand during holidays and under unexpected events is also presented.Meanwhile,a computer software is developed.Through actual application,this method performs well and has high accuracy,so it can be applied to the daily operation of a water distribution system and lay a foundation for on-line optimal operation.
文摘Recently, much dispute has occurred about the validity of the New Keynesian model from both theoretical and empirical views. However, a few studies have analyzed this model from the empirical perspective. Few other studies have analyzed this model directly or nearly directly. This article empirically examines the New Keynesian model focusing on inflation forecast. Generalized method of moments (GMM) is used to examine whether the typical Keynesian model with Taylor rule is empirically appropriate for the US, UK, Euro area, and Japan. The results showed: (1) the New Keynesian model fits well in most cases and explains the real economy well. Taylor rule also fits well for most cases; (2) Rational expectations for inflation rates may not be useful based on this model When AR (1) (time series analysis) model is used to capture inflation expectations instead of one-time ahead real values, the model fits well. With measured expectations, the relative weight of the forward-looking terms increase on the cost of lagged inflation and output terms, even up to the point at which the lagged inflation terms are no longer needed to rescue the new Keynesian model; and (3) Forward-looking variables play more important roles than backward-looking ones in economic activity. Results with expectations with forward-looking terms perform better in general. This New Keynesian model may reduce the importance of lagged output in some cases
基金supported by a grant from Payame Noor University, Tehran-Iran
文摘Forecasting exchange rate is undoubtedly an attractive and challenging issue that has been of interest in different domains for many years. The singular spectrum analysis (SSA) technique has been used as a promising technique for time series forecasting including exchange rate series. The SSA technique is based upon two main choices: Window length, L, and the number of singular values, r. These values are very important for the reconstruction stage and forecasting purposes. Here the authors consider an optimum version of the SSA technique for forecasting exchange rates. The forecasting performances of the SSA technique for one-step-ahead forecast of six exchange rate series are used to find the best L and r.
基金supported by a grant (No. 88/121230) from Institute for Trade StudiesResearch (ITSR), Tehran, Iran
文摘This paper describes the methodology of singular spectrum analysis (SSA) and demonstratethat it is a powerful method of time series analysis and forecasting,particulary for economic time series.The authors consider the application of SSA to the analysis and forecasting of the Iranian nationalaccounts data as provided by the Central Bank of the Islamic Republic of Iran.
基金The project is supported by National Natural Science Foundation of China (30400275) Science Found for Distinguished Young Scholars of Heilong, iiang (QC04C28)
文摘The advantage of artificial neural network and wavelet analysis are integrated through replacing the traditional S-shaped activation function with the wavelet function. One method of chaotic prediction based on wavelet BP network was put forward based on the reconstruction of state space. Training data construction and networks structure are determined by chaotic phase space, and nonlinear relationship of phase points was established by BP neural networks. As an example, the new method was applied on short term forecasting of monthly precipitation time series of Sanjiang Plain with chaotic characteristics. The results showed so higher precision of the method had that the theoretical evidence would be provided for applying the chaos theory to study the variable law of monthly precipitation.