precipitation is one of important parameters of climatology and atmospheric science that have more importance in human life. recently, extensive flood and drought entered many damage to most parts of the world. precipitation forecasting and alerts management role is responsible for these problems. today, artificial neural networks are one of developed method that applied for estimate and predic...

This paper presents a predictive study applied to a manufacturing equipment in order to predict malfunctions, and consequently enabling predictive maintenance practices. ARIMA forecasting methods are successfully compared with neural networks models, both used over data obtained from a monitoring system that continuously keeps track of the relevant equipment parameters. The results show that bo...

<span>The main objective of stock market investors is to maximize their gains. As a result, price forecasting has not lost interest in recent decades. Nevertheless, prices are influenced by news, rumor, and various economic factors. Moreover, the characteristics specific markets can differ significantly between countries regions, based on size, liquidity, regulations. Accordingly, it diff...

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 ...

Forecasting accuracy is one of the most favorable critical issues in Autoregressive Integrated Moving Average (ARIMA) models. The study compares the application of two forecasting methods on the amount of Taiwan export, the Fuzzy time series method and ARIMA method. Model discussed for the ARIMA method and Fuzzy time series method include the Sturges rules. When the sample period is extend in o...