Prediction of Gas Consumption

نویسندگان

  • Jiří Klema
  • Jan Kout
چکیده

This paper deals a universal prediction system based on AI techniques and classical statistical analysis. It describes principles and methodologies used within the system. Further it discusses internal structure of the system and general conditions for its successful use. Despite of system wide applicability, originally it was conceived as a system for prediction of gas consumption. A practically oriented part of the paper reports on the gas consumption problem domain and an application of the system to the domain.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

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

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. ...

متن کامل

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

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. ...

متن کامل

تحلیل آماری و برآورد فاصله اطمینان پیش‌بینی شبکه عصبی ترکیبی به منظور مقایسه با مدل خطی ARIMA: مطالعه موردی مصرف ماهانه گاز طبیعی در بخش خانگی ایران

As one of the important energy forms, natural gas consumption has an upward trend in recent years. Therefore management and planning for provision of it requires prediction of the future consumption. But many of prediction procedures are inherently stochastic therefore it is important to have better knowledge about the robustness of prediction procedures. This paper compares robustness of two p...

متن کامل

The Forecasting of Iran Natural Gas Consumption Based On Neural-Fuzzy System Until 2020

In this paper, an Adaptive-Network-based Fuzzy Inference System (ANFIS) is used for forecasting of natural gas consumption. It is clear that natural gas consumption prediction for future, surly can help Statesmen to decide more certain. There are many variables which effect on gas consumption but two variables that named Gross Domestic Product (GDP) and population, are selected as two input var...

متن کامل

An Artificial Neural Network Model for Prediction of the Operational Parameters of Centrifugal Compressors: An Alternative Comparison Method for Regression

Nowadays, centrifugal compressors are commonly used in the oil and gas industry, particularly in the energy transmission facilities just like a gas pipeline stations. Therefore, these machines with different operational circumstances and thermodynamic characteristics are to be exploited according to the operational necessities. Generally, the most important operational parameters of a gas pipel...

متن کامل

Forecasting Natural Gas Demand Using Meteorological Data: Neural Network Method

The need for prediction and patterns of gas consumption especially in the cold seasons is essential for consumption management and policy planning decision making. In residential and commercial uses which account for the bulk of gas consumption in the country the effects of meteorological variables have the highest impact on consumption.  In the present research four variables include daily ave...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1999