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Forecasting of the rice yields time series forecasting using artificial neural network and statistical model

Accurate forecasting of the rice yields is very important for the organization to make a better planning and decision making. In this study, a hybrid methodology that combines the individual forecasts based on artificial neural network (CANN) approach for modeling rice yields was investigated. The C...

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Main Authors: Shabri, Ani, Samsudin, Ruhaidah, Ismail, Zuhaimy
Format: Article
Published: Asian Network for Scientific lnforrnation 2009
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/18982/
https://doi.org/10.3923/jas.2009.4168.4173
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spelling my.utm.189822018-03-15T01:20:37Z http://eprints.utm.my/id/eprint/18982/ Forecasting of the rice yields time series forecasting using artificial neural network and statistical model Shabri, Ani Samsudin, Ruhaidah Ismail, Zuhaimy QA75 Electronic computers. Computer science Accurate forecasting of the rice yields is very important for the organization to make a better planning and decision making. In this study, a hybrid methodology that combines the individual forecasts based on artificial neural network (CANN) approach for modeling rice yields was investigated. The CANN has several advantages compared with conventional Artificial Neural Network (ANN) model, the statistical the autoregressive integrated moving average (ARIMA) and exponential smoothing (EXPS) model in order to get more effective evaluation. To assess the effectiveness of these models, we used 38 years of time series records for rice yield data in Malaysia from 1971 to 2008. Results show that the CANN model appears to perform reasonably well and hence can be applied to real-life prediction and modeling problems. Asian Network for Scientific lnforrnation 2009 Article PeerReviewed Shabri, Ani and Samsudin, Ruhaidah and Ismail, Zuhaimy (2009) Forecasting of the rice yields time series forecasting using artificial neural network and statistical model. Journal of Applied Sciences, 9 (23). pp. 4168-4173. ISSN 1812-5654 https://doi.org/10.3923/jas.2009.4168.4173 DOI:10.3923/jas.2009.4168.4173
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Shabri, Ani
Samsudin, Ruhaidah
Ismail, Zuhaimy
Forecasting of the rice yields time series forecasting using artificial neural network and statistical model
description Accurate forecasting of the rice yields is very important for the organization to make a better planning and decision making. In this study, a hybrid methodology that combines the individual forecasts based on artificial neural network (CANN) approach for modeling rice yields was investigated. The CANN has several advantages compared with conventional Artificial Neural Network (ANN) model, the statistical the autoregressive integrated moving average (ARIMA) and exponential smoothing (EXPS) model in order to get more effective evaluation. To assess the effectiveness of these models, we used 38 years of time series records for rice yield data in Malaysia from 1971 to 2008. Results show that the CANN model appears to perform reasonably well and hence can be applied to real-life prediction and modeling problems.
format Article
author Shabri, Ani
Samsudin, Ruhaidah
Ismail, Zuhaimy
author_facet Shabri, Ani
Samsudin, Ruhaidah
Ismail, Zuhaimy
author_sort Shabri, Ani
title Forecasting of the rice yields time series forecasting using artificial neural network and statistical model
title_short Forecasting of the rice yields time series forecasting using artificial neural network and statistical model
title_full Forecasting of the rice yields time series forecasting using artificial neural network and statistical model
title_fullStr Forecasting of the rice yields time series forecasting using artificial neural network and statistical model
title_full_unstemmed Forecasting of the rice yields time series forecasting using artificial neural network and statistical model
title_sort forecasting of the rice yields time series forecasting using artificial neural network and statistical model
publisher Asian Network for Scientific lnforrnation
publishDate 2009
url http://eprints.utm.my/id/eprint/18982/
https://doi.org/10.3923/jas.2009.4168.4173
_version_ 1643647033381224448
score 13.214268

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