Radar data analysis using linear regression

Authors

  • Anjali Banerjee Dept. of Computer Engineering, SVPCET, Nagpur, MH, India
  • Dr. Sunil M. Wanjari Dept. of Computer Engineering, SVPCET, Nagpur, MH, India
  • Mr. Brijesh Kanaujiya Reginal Metrological Centre, IMD, Delhi, India
  • Ashwin George Dept. of Computer Engineering, SVPCET, Nagpur, MH, India
  • Harshali Hood Dept. of Computer Engineering, SVPCET, Nagpur, MH, India
  • Ryan Chettiar SVPCET, Nagpur, MH, India

Keywords:

Radar Analysis, Linear Regression, Weather Elements, Correction

Abstract

The unpredictable fluctuations in weather and atmospheric conditions have made weather forecasting an important subject of study. Scientists have created innovative techniques for training models to acquire precision over nonlinear statistical datasets over the past few decades to avert further environmental harm and global calamities. A new dimension to the field of weather forecasting has been added by Artificial intelligence and machine learning that requires only a few confusing mathematical equations. The motive of this examination is to analyze radar data. The implications of this study will feed into the field of climate prediction and weather forecast models. This research also shows a proposed model that demonstrates the correlation between different radar elements.
Keywords- Radar Analysis, Linear Regression, Weather Elements, Correction

References

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Published

29-04-2023

How to Cite

Anjali Banerjee, Dr. Sunil M. Wanjari, Mr. Brijesh Kanaujiya, Ashwin George, Harshali Hood, & Ryan Chettiar. (2023). Radar data analysis using linear regression. International Journal for Research Publication and Seminar, 14(3), 67–72. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/469

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Section

Original Research Article

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