Abstract:

Rainfall prediction is the one of the important technique to predict the climatic conditions in any country. This paper proposes a rainfall prediction model using Multiple Linear Regression (MLR) for Indian dataset. The input data is having multiple meteorological parameters and to predict the rainfall in more precise. The Mean Square Error (MSE), accuracy, correlation are the parameters used to validate the proposed model. From the results, the proposed machine learning model provides better results than the other algorithms in the literature.

 introduction

Rainfall prediction is important in Indian civilization and it plays major role in human life to a great extent. It is demanding responsibility of meteorological department to predict the frequency of rainfall with uncertainty. It is complicated to predict the rainfall accurately with changing climatic conditions. It is challenging to forecast the rainfall for both summer and rainy seasons. Researchers in all over the world have developed various models to predict the rain fall mostly using random numbers and they are similar to the climate data.

The proposed model is developed using multiple linear regression. The proposed method uses Indian meteorological date to predict the rain fall. Usually machine learning algorithms are classified into two major categories: (i) unsupervised learning (ii) supervised learning. All the clustering algorithms come under supervised machine learning. Figure 1 represents the different classification of machine learning algorithms. Figure 2 describes the rainfall prediction research based on neural network for Indian scenario. Even though many models have developed, but it is necessary for doing research using machine learning algorithms to get accurate prediction. The error free prediction provides better planning in the agriculture and other industries.

This paper is organized as follows: Section II discuses the various related methods in the literature, Section III explains the proposed method MLR based Rain Fall Prediction. Results are elaborated in section IV and Section V concludes the paper.

existing approach or algorithm

Rainfall prediction is important in Indian civilization and it plays major role in human life to a great extent. It is demanding responsibility of meteorological department to predict the frequency of rainfall with uncertainty. It is complicated to predict the rainfall accurately with changing climatic conditions. It is challenging to forecast the rainfall for both summer and rainy seasons. Researchers in all over the world have developed various models to predict the rain fall mostly using random numbers and they are similar to the climate data.

Rainfall prediction is the one of the important technique to predict the climatic conditions in any country. This paper proposes a rainfall prediction model using Multiple Linear Regression (MLR) for Indian dataset. The input data is having multiple meteorological parameters and to predict the rainfall in more precise. The Mean Square Error (MSE), accuracy, correlation are the parameters used to validate the proposed model. From the results, the proposed machine learning model provides better results than the other algorithms in the literature

Proposed System

The proposed model is developed using multiple linear regression. The proposed method uses Indian meteorological date to predict the rain fall. Usually machine learning algorithms are classified into two major categories: (i) unsupervised learning (ii) supervised learning. All the clustering algorithms come under supervised machine learning. Figure 1 represents the different classification of machine learning algorithms. Figure 2 describes the rainfall prediction research based on neural network for Indian scenario. Even though many models have developed, but it is necessary for doing research using machine learning algorithms to get accurate prediction. The error free prediction provides better planning in the agriculture and other industries.

Algorithms

Decision Tree

Random Forest Tree

SYSTEM REQUIREMENTS
SOFTWARE REQUIREMENTS:
• Programming Language : Python
• Font End Technologies : TKInter/Web(HTML,CSS,JS)
• IDE : Jupyter/Spyder/VS Code
• Operating System : Windows 08/10

HARDWARE REQUIREMENTS:

 Processor : Core I3
 RAM Capacity : 2 GB
 Hard Disk : 250 GB
 Monitor : 15″ Color
 Mouse : 2 or 3 Button Mouse
 Key Board : Windows 08/10