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首页> 外文期刊>Advances in Natural and Applied Sciences >Decision Tree Based Rainfall Prediction Model with Data Driven Model using Multiple Linear Regression
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Decision Tree Based Rainfall Prediction Model with Data Driven Model using Multiple Linear Regression

机译:数据驱动模型的多元线性回归决策树降雨预报模型

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Meteorological data mining is a form of data mining concerned with finding hidden patterns inside largely available meteorological data, so that the information retrieved can be transformed into usable knowledge. Weather is one of the meteorological data that is rich in important knowledge. The most important climatic element which impacts on agricultural sector is rainfall. Thus rainfall prediction becomes an important issue in agricultural country like India. In this paper, here use data mining technique in forecasting monthly Rainfall of Tamil Nadu. This was carried out using traditional statistical technique -Multiple Linear Regression. The data include the year 2016 collected locally from Regional Meteorological Center, Chennai, Tamil Nadu, India.
机译:气象数据挖掘是一种数据挖掘的形式,它涉及在大量可用的气象数据中查找隐藏模式,以便将检索到的信息转换为可用的知识。天气是富含重要知识的气象数据之一。影响农业部门的最重要的气候要素是降雨。因此,在印度等农业国家,降雨预报成为重要问题。本文采用数据挖掘技术来预测泰米尔纳德邦的每月降雨量。这是使用传统的统计技术-多元线性回归进行的。数据包括从印度泰米尔纳德邦钦奈地区气象中心本地收集的2016年。

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