Time Series Modeling for Forecasting Wheat Production of Pakistan

نویسندگان

  • M. Amin
  • M. Amanullah
چکیده

Wheat is the main agriculture crop of Pakistan. For country planning, forecasting is the main tool for predicting the production of wheat to determine the situation what would be the value of production coming year. In this research, we developed time series models and best model is identified for the objective to forecast the wheat production of Pakistan. In this research large time periods i.e. 1902-2005 data was used. Various time series models are fitted on this data using two software’s JMP and Statgraphics. We have found that the best model is ARIMA (1, 2, 2). On the basis of this selected model, we have found that wheat production of Pakistan would become 26623.5 thousand tons in 2020 and would become double in 2060 as compared in 2010.

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

Structural Breaks, Automatic Model Selection and Forecasting Wheat and Rice Prices for Pakistan

Structural breaks and existence of outliers in time series variables results in misleading forecasts. We forecast wheat and rice prices by capturing the exogenous breaks and outliers using Automatic modeling. The procedure identifies the outliers as the observations with large residuals. The suggested model is compared on the basis of Root Mean Square Error (RMSE) and Mean Absolute Percentage E...

متن کامل

Wheat Yield Forecasting for Punjab Province from Vegetation Index Time Series and Historic Crop Statistics

Policy makers, government planners and agricultural market participants in Pakistan require accurate and timely information about wheat yield and production. Punjab Province is by far the most important wheat producing region in the country. The manual collection of field data and data processing for crop forecasting by the provincial government requires significant amounts of time before offic...

متن کامل

AN EXTENDED FUZZY ARTIFICIAL NEURAL NETWORKS MODEL FOR TIME SERIES FORECASTING

Improving time series forecastingaccuracy is an important yet often difficult task.Both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. In this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...

متن کامل

Rainfall-runoff process modeling using time series transfer function

Extended Abstract 1- Introduction Nowadays, forecasting and modeling the rainfall-runoff process is essential for planning and managing water resources. Rainfall-Runoff hydrologic models provide simplified characterizations of the real-world system. A wide range of rainfall-runoff models is currently used by researchers and experts. These models are mainly developed and applied for simulation...

متن کامل

Stochastic Monthly Rainfall Time Series Analysis, Modeling and Forecasting ( A cas study: Ardebilcity

Rainfall is the main source of the available water for human. Predicting the amount of the future rainfall is useful for informed policies, planning and decision making that will help potentially make optimal and sustainable use of available water resources. The main aim of this study was to investigate the trend and forecast monthly rainfall of selected synoptic station in Ardabil province usi...

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 2014