Design and Implementation of Rainfall Prediction Model using Supervised Machine Learning Data Mining Techniques
Priti Sharma1, Deepak Sharma2
1Deepak Sharma, Research Scholar, Department of Computer Science and applications, MD University, Rohtak (Haryana), India.
2Dr. Priti Sharma, Assistant Professor, Department of Computer Science and applications, MD University, Rohtak (Haryana), India.
Manuscript received on 12 October 2021 | Revised Manuscript received on 28 October 2021 | Manuscript Accepted on 15 November 2021 | Manuscript published on 30 November 2021 | PP: 20-26 | Volume-1 Issue-2 November 2021 | Retrieval Number: 100.1/ijdm.B1615111221 | DOI:10.54105/ijdm.B1615.111221
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Abstract: Data mining is a rapidly developing technology that has enriched a lot of field such as business analysis, market analysis, weather forecasting, stock market analysis and many more. It starts with collecting data sets from reliable sources and pre-processing that data. There are some anomalies associated with data collected in large volumes such as outliers, missing values, and duplicated values. Remove these kinds of anomalies is teamed as pre-processing of data. In this paper, collection of weather data and pre-processing it for rainfall prediction model using Rapid Miner tool has been discussed. Also, artificial neural network data mining techniques is used to design a rainfall prediction model. ANN classification techniques is a complex data mining technique results in high accuracy in prediction of rainfall.
Keywords: Data Mining, Artificial Neural Network (ANN), Classification Techniques, Cross Validation, Rapid Miner
Scope: Data Mining