Data mining techniques for rainfall prediction in the Tepi region of Ethiopia

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Agriculture depends mainly on the rainfall especially in countries like Ethiopia (Africa) as irrigation system is not much in practice. One of the main reasons is because of its natural topography. Though there are many factors that affect the agricultural yield, it is appropriate to consider the main factor rainfall that decides about the food production. The prediction of the rainfall can be done by using different techniques like regression analysis, clustering, artificial neural network (ANN) and fuzzy logic. Therefore, the significance of this research is essential for the Tepi region in the south west part of Ethiopia (SNNPR) where agriculture is the main occupation of the people living here. This research is first of its kind conducted in this region, and this paper shows the result related with the rainfall prediction by using LR – Linear Regression technique for the early prediction of the next consecutive three (3) years based on the previous available rainfall data.

     

     


  • Keywords


    Data Mining; Rainfall Prediction; Linear Regression; Agriculture.``

  • References


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Article ID: 14150
 
DOI: 10.14419/ijag.v6i2.14150




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