Rainfall Prediction Using Data Mining Techniques - A Survey

Kavitha Rani B, Govardhan A
2013 Computer Science & Information Technology ( CS & IT )   unpublished
Rainfall is considered as one of the major components of the hydrological process; it takes significant part in evaluating drought and flooding events. Therefore, it is important to have an accurate model for rainfall prediction. Recently, several data-driven modeling approaches have been investigated to perform such forecasting tasks as multilayer perceptron neural networks (MLP-NN). In fact, the rainfall time series modeling (SARIMA) involvesimportant temporal dimensions. In order to evaluate
more » ... the incomes of both models, statistical parameters were used to make the comparison between the two models. These parameters include the Root Mean Square Error RMSE, Mean Absolute Error MAE, Coefficient Of Correlation CC and BIAS. Two-Third of the data was used for training the model and One-third for testing.
doi:10.5121/csit.2013.3903 fatcat:fplyx4nakbgylm4u5z5r3yzfzq