Hybrid Prediction Models for Rainfall Forecasting

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Aim:

Analyze the rainfall data from database for rainfall prediction

Existing System:

The dataset is stored and processed in structured database like MySQL, Oracle etc. The time consumed to process volumes of data to pre-process and classify were huge. The model is utilized to generate the prediction of future rainfall based on the dataset. MySQL is a flexible computing framework suitable for small applications. Therefore MySQL was used as simple computing and storage platform.

Proposed System:

To overcome the fallback in the existing system we propose a machine learning based system to increase the efficiency and accuracy. To handle voluminous data we are using Hadoop to store and retrieve data from the distributed hadoop file system (hdfs). Hadoop allows the user to load data into a cluster. Random forest algorithm is to be implemented for forecasting rainfall.