A Review on Weather Forecasting using R

Authors

  • Pritam Sah  Tulsiramji Gaikwad Patil College of Engineering and Technology, Wardha Road, Nagpur, Maharashtra, India
  • Prof. Jayant Adhikari   Tulsiramji Gaikwad Patil College of Engineering and Technology, Wardha Road, Nagpur, Maharashtra, India
  • Prof. Rajesh Babu  Tulsiramji Gaikwad Patil College of Engineering and Technology, Wardha Road, Nagpur, Maharashtra, India

Keywords:

R programming, Logistic Regression, Decision Tree, Random Forest, independent variable, dependent variable.

Abstract

In this project, we are forecasting whether rain may occur or not in the coming day. We are using public data to implement this. We are using 3 algorithms in this project viz. Logistic Regression, Decision Tree and Random Forest which is implemented using R programming. 3 algorithms are being used just to improve the efficiency of our project. In our dataset we will have different parameters or fields (independent variables) like Wind Speed, Wind Direction etc. that will affect dependent variable i.e. RainTomorrow. After applying algorithms on different fields of dataset i.e. independent variable and dependent variable, we will predict whether rain fall will occur or not.

References

  1. Sanjay Chakraborty, N.K.Nagwani, Lopamudra Dey “Weather Forecasting using Incremental K-Means clustering”, in CiiT International Journal of Data Mining & Knowledge Engineering, May 2012
  2. M.Kannan, S.Prabhakaran, P.Ramachandran, “Rainfall Forecasting Using Data Mining Technique”, International Journal of Engineering and Technology Vol.2 (6), 397-401, 2010.

International Journal of Scientific Research in Science and Technology

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Published

2018-06-30

Issue

Volume 4, Issue 8, May-June-2018

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Pritam Sah, Prof. Jayant Adhikari , Prof. Rajesh Babu, " A Review on Weather Forecasting using R, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 4, Issue 8, pp.555-557, May-June-2018.