the present research was planned to evaluate the skill of linear stochastic models known as arima and multiplicative seasonal autoregressive integrated moving average (sarima) model in the quantitative forecasting of the standard runoff index (sri) in karkheh basin. to this end, sri was computed in monthly and seasonal time scales in 10 hydrometric stations in 1974-75 to 2012-13 period of time ...

this study aims to evaluate the link between economic growth and consumer price index (cpi) in japan for the period of 1980-2014. initial series were adjusted for stationarity using the augmented dickey- fuller (adf) test for unit root followed by the application of johansen co-integration test in order to examine the long-run relationship among the variables, while the causalities were evaluat...

Modeling and analysis of future prices has been hot topic for economic analysts in recent years. Traditionally, the complex movements in the prices are usually taken as random or stochastic process. However, they may be produced by a deterministic nonlinear process. Accuracy and efficiency of economic models in the short period forecasting is strategic and crucial for business world. Nonlinear ...

in recent years, various time series models have been proposed for financial markets forecasting. in each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. many researchers have compared different time series models together in order to determine more efficient ...

introduction: studying the hydrological cycle, especially in large scales such as water catchments, is difficult and complicated despite the fact that the numbers of hydrological components are limited. this complexity rises from complex interactions between hydrological components and environment. recognition, determination and modeling of all interactive processes are needed to address this i...

improving time series forecastingaccuracy is an important yet often difficult task.both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. in this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...