نتایج جستجو برای: time series models
تعداد نتایج: 2833043 فیلتر نتایج به سال:
Using quarterly Taiwan economic data, we demonstrate that deeper understanding of relations between variables and substantial gains in forecasting can be obtained by applying econometric and statistical tools to the traditional macroeconometric models. The improvement in forecasting accuracy is illustrated by outof-sample forecasts, and the models employed in the comparison include univariate t...
in the management of river basins, prediction of river water quality is essential to maintain water quality within standard limits. this study performed a time-series analysis of the prediction of chlorine concentration and electrical conductivity time series data for the period of 1991-2005 from sefidrood river in northern iran. the seasonal prediction of chlorine and electrical conductivity t...
Considering the fact that natural gas is a widely used energy source, the prediction of its consumption can be useful (Derek LAM, 2013). As Iran has one of the largest gas reserves in the world, its consumption in the country can affect the worldwide price of gas, Therefore, the current research is useful both from economic and environmental point of view. ...
Due to the important role of climatic parameters such as radiation, temperature, precipitation and evaporation rate in water resources management, this study employed time series modeling to forecast climatic parameters. After normality test of the parameters, nonparametric Mann-Kendall test was used in order to do trend analysis of data at P-value<0.05. Relative humidity and evaporation (with ...
computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. nowadays, despite the numerous time series forecasting models propos...
Accurate estimation of suspended sediment in rivers is very important from different aspects including agriculture, soil conservation, shipping, dam construction and aquatic research. There are different methods for suspended sediment estimation. In the present study to evaluate the ability of time-series models including Markov and ARIMA in predicting suspended sediment and to compare their re...
In this paper, one of the most important criterion in public services quality named availability is evaluated by using artificial neural network (ANN). In addition, the availability values are predicted for future periods by using exponential weighted moving average (EWMA) scheme and some time series models (TSM) including autoregressive (AR), moving average (MA) and autoregressive moving avera...
In this paper, we show that the Chapman-Kolmogorov formula could be used as a recursive formula for computing the m-step-ahead conditional density of a Markov bilinear model. The stationary marginal probability density function of the model may be approximated by the m-step-ahead conditional density for sufficiently large m.
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