@article{(Open Science Index):https://publications.waset.org/pdf/15031,
	  title     = {Empirical Statistical Modeling of Rainfall Prediction over Myanmar},
	  author    = {Wint Thida Zaw and  Thinn Thu Naing},
	  country	= {},
	  institution	= {},
	  abstract     = {One of the essential sectors of Myanmar economy is
agriculture which is sensitive to climate variation. The most
important climatic element which impacts on agriculture sector is
rainfall. Thus rainfall prediction becomes an important issue in
agriculture country. Multi variables polynomial regression (MPR)
provides an effective way to describe complex nonlinear input output
relationships so that an outcome variable can be predicted from the
other or others. In this paper, the modeling of monthly rainfall
prediction over Myanmar is described in detail by applying the
polynomial regression equation. The proposed model results are
compared to the results produced by multiple linear regression model
(MLR). Experiments indicate that the prediction model based on
MPR has higher accuracy than using MLR.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {10},
	  year      = {2008},
	  pages     = {3418 - 3421},
	  ee        = {https://publications.waset.org/pdf/15031},
	  url   	= {https://publications.waset.org/vol/22},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 22, 2008},
	}