期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2021
卷号：9
期号：7
页码：9069-9076
DOI：10.15680/IJIRCCE.2021.0907214
语种：English
出版社：S&S Publications
摘要：One of the most significant approaches for predicting meteorological conditions in any country is rainfall prediction. Rainfall is caused by a variety of natural elements such as temperature, humidity, cloudiness, wind speed, and so on. Rainfall forecasting is a crucial problem for meteorological departments since it is so intimately linked to the economy and human survival.Four machine learning algorithms have been applied on a selected set of features from the dataset to achieve an higher accuracy. This work proposes a rainfall prediction model using Multiple Linear Regression (MLR) for Indian dataset. The parameters considered for training the model includes the daily recorded temperature, humidity, cloud speed, wind speed and wind direction. The input data is having multiple meteorological parameters and to predict the rainfall in more precise. The suggested model is validated using the Mean Square Error (MSE), accuracy, and correlation metrics. This system is a modified framework that uses data analysis and machine learning methods to blend observed and estimated information to predict rainfall. From the results, the proposed machine learning model which consists of four algorithms for the analysis provides better results than the other algorithms used in the existing system.
