Modeling of Regression-Based Rainfall Prediction over Myanmar

摘要：

The most important climatic element which impacts on agriculture sector is rainfall. Therefore rainfall prediction becomes an important issue in the domain of agriculture. Multi variables polynomial regression (MPR) is a statistical method used to describe complex nonlinear input output relationships. The main contribution of this paper is to implement the rainfall prediction model over Myanmar using MPR. We compare the proposed model results 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.

关键词： statistical modeling polynomial regression rainfall prediction

作者: Wint Thida Zaw Thinn Thu Naing

作者单位: University of Computer Studies, Yangon, Myanmar

会议类型: 国际会议

会议名称: The 9th International Symposium on Knowledge and Systems Sciences,The 4th Asia-Pacific International Conference on Knowledge Management(第九届国际知识与系统科学学术年会暨第四届亚太国际知识管理年会)

会议地点: 广州

会议语种:英文

页码: 365-369

在线出版日期: 2008-12-11（万方平台首次上网日期，不代表论文的发表时间）