Design and Implementation of Rainfall Prediction Model using Supervised Machine Learning Data Mining Techniques

D. Sharma, Dr. Priti Sharma
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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.
基于监督式机器学习数据挖掘技术的降雨预测模型设计与实现
数据挖掘是一项快速发展的技术,它丰富了商业分析、市场分析、天气预报、股票市场分析等许多领域。首先要从可靠的来源收集数据集,并对这些数据进行预处理。大量收集的数据有一些异常,如异常值、缺失值和重复值。消除这类异常被称为数据的预处理。本文讨论了利用Rapid Miner工具收集气象数据并对其进行预处理以建立降雨预报模型。同时,利用人工神经网络数据挖掘技术设计了降雨预测模型。人工神经网络分类技术是一种复杂的数据挖掘技术,具有较高的预测精度。
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