The demand forecasting is essential for all production and non-production systems. However, nowadays there are only few researches on this area. Most of researches somehow benefited from simulation in the conditions of demand uncertainty. But this paper presents an iterative method to find most probable stochastic demand point with normally distributed and independent variables of n-dime...

time series forecasting is an active research area that has drawn considerable attention for applications in a variety of areas. forecasting accuracy is one of the most important features of forecasting models. nowadays, despite the numerous time series forecasting models which have been proposed in several past decades, it is widely recognized that financial markets are extremely difficult to ...

Petroleum (crude oil) is one of the most important resources of energy and its demand and consumption is growing while it is a non-renewable energy resource. Hence forecasting of its demand is necessary to plan appropriate strategies for managing future requirements. In this paper, three types of time series methods including univariate Seasonal ARIMA, Winters forecasting and Transfer Function-...

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...

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...

  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 efficien...

An organization has to make the right decisions in time depending on demand information to enhance the commercial competitive advantage in a constantly fluctuating business environment. Therefore, estimating the demand quantity for the next period most likely appears to be crucial. The objective of the paper is to propose a new forecasting mechanism which is modeled by artificial intelligence a...