@article{
 title = {Comparison of ARIMA and Neural Network Model to Forecast the Jute Production in Bangladesh},
 type = {article},
 year = {2017},
 keywords = {ARIMA,Forecasting,Jute Production,Neural Network},
 pages = {11-18},
 volume = {40},
 id = {36e3fc73-5bad-37a7-87d5-3b21c3bee0b3},
 created = {2020-11-12T22:07:42.006Z},
 file_attached = {true},
 profile_id = {3d6b17c2-7de8-3a82-bf4f-ddb0e3081e5f},
 last_modified = {2021-05-05T17:29:59.458Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bangladesh is a famous for jute production since 1971 and earned a significant amount of foreign currency by exporting jute and jute products to different countries. This paper compares the accuracy of forecasting jute productions in Bangladesh of the two models namely Auto-Regressive Integrated Moving Average (ARIMA) and Neural Network (NN). However, this paper considers a secondary data set of yearly jute production in Bangladesh over the period 1972 to 2013. Results of this paper shown that the Neural Network (NN) model performs better than ARIMA model to forecast the jute production in Bangladesh. Therefore, this paper suggests using NN model to forecast the jute productions in Bangladesh.},
 bibtype = {article},
 author = {Hossain, Md Moyazzem and Abdulla, Faruq and Hossain, Zakir},
 journal = {Jahangirnagar University Journal of Science},
 number = {1}
}

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