Time Series Models to Predict the Monthly and Annual Consumption of Natural Gas in Iran

Authors

  • Arash Farrokhi Department of Industrial Engineering, University College of Ayandegan, Tonekabon, Iran
  • Reza Hassanzadeh Department of Industrial Engineering, University College of Rouzbahan, Sari,, Iran, Iran
Abstract:

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. The goal of the study is to select the best model for the prediction of gas consumption. To achieve the goal time series analysis are used.   The findings indicate that ARIMA (0, 1, 0) is the best model for the prediction of annual gas consumption, while SARIMA (1, 0, 0) (1, 1, 0) for the prediction of monthly gas consumption

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

a time-series analysis of the demand for life insurance in iran

با توجه به تجزیه و تحلیل داده ها ما دریافتیم که سطح درامد و تعداد نمایندگیها باتقاضای بیمه عمر رابطه مستقیم دارند و نرخ بهره و بار تکفل با تقاضای بیمه عمر رابطه عکس دارند

Development of Markov Chain Grey Regression Model to Forecast the Annual Natural Gas Consumption

Accurate forecasting of annual gas consumption of the country plays an important role in energy supply strategies and policy making in this area.  Markov chain grey regression model is considered to be a superior model for analyzing and forecasting annual gas consumption.  This model Markov is a combination of the Markov chain and grey regression models. According to this model, the residual er...

full text

Comparative Study Among Different Time Series Models for Monthly Rainfall Forecasting in Shiraz Synoptic Station, Iran

In this research, monthly rainfall of Shiraz synoptic station from March 1971 to February 2016 was studied using different time series models by ITSM Software. Results showed that the ARMA (1,12) model based on Hannan-Rissanen method was the best model which fitted to the data. Then, to assess the verification and accuracy of the model, the monthly rainfall for 60 months (from March 2011 to Feb...

full text

the survey of the virtual higher education in iran and the ways of its development and improvement

این پژوهش با هدف "بررسی وضعیت موجود آموزش عالی مجازی در ایران و راههای توسعه و ارتقای آن " و با روش توصیفی-تحلیلی و پیمایشی صورت پذیرفته است. بررسی اسنادو مدارک موجود در زمینه آموزش مجازی نشان داد تعداد دانشجویان و مقاطع تحصیلی و رشته محل های دوره های الکترونیکی چندان مطلوب نبوده و از نظر کیفی نیز وضعیت شاخص خدمات آموزشی اساتید و وضعیت شبکه اینترنت در محیط آموزش مجازی نامطلوب است.

Evaluation of SARIMA time series models in monthly streamflow estimation in Idanak hydrometry station

prediction of hydrological variables is a highly effective tool in water resource management. One of the important tools for modeling hydrological processes is the use of time series modeling and analysis. River series production series can be used by time series models in various studies such as drought, flood, reservoir systems design and many other purposes For this purpose, monthly flow dat...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 2  issue 2

pages  67- 76

publication date 2017-05-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023