Application of data mining tools for rice yield prediction on clustered regions of Bangladesh

Author

Rahman, Mohammad Motiur ; Haq, Naheena ; Rahman, Rashedur M.

Author_Institution

Electr. & Comput. Eng. Dept., North South Univ., Dhaka, Bangladesh

fYear

2014

Firstpage

8

Lastpage

13

Abstract

Reservation of adequate food is a major concern for many developing countries worldwide. Governments of those countries also want to meet the demand of food in the long term, especially during the period of natural calamity. For low lying region such as Bangladesh, predicting the supply of food is critical. Besides, rice productivity of Bangladesh has also changed due to varying climatic over the last couple of decades. In this paper, a comprehensive analysis has been made to forecast the rice yield of Bangladesh.

Keywords

agricultural products; data mining; food products; pattern clustering; productivity; Bangladesh clustered regions; data mining tools; developing countries; food demand; food reservation; rice productivity; rice yield; rice yield prediction; Agriculture; Computers; Linear regression; Meteorology; Regression tree analysis; Testing; Training; Self organizing maps(SOM); decision tree; ensemble learning; k-means clustering; linear regression; neural network; regression tree;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology (ICCIT), 2014 17th International Conference on

Type

conf

DOI

10.1109/ICCITechn.2014.7073081

Filename

7073081