COMPARING DIFFERENT COLOUR MODELS USED FOR ANALYSIS OF RADAR DATA

Authors

  • Rishi Nandan Dept. of Computer Engineering, SVPCET, Nagpur, MH, India
  • Dr. Sunil M. Wanjari Dept. of Computer Engineering, SVPCET, Nagpur, MH, India
  • Mr. Brijesh Kanaujiya Dept. of Computer Engineering, SVPCET, Nagpur, MH, India
  • Pranjali Meshram Dept. of Computer Engineering, SVPCET, Nagpur, MH, India
  • Devyani Adchule Dept. of Computer Engineering, SVPCET, Nagpur, MH, India
  • Punit Sharma Dept. of Computer Engineering, SVPCET, Nagpur, MH, India

Keywords:

Weather forecasting, Elements, Accuracy, colour models

Abstract

Researchers have been working for decades todevelop a model that can predict the weather with maximum accuracy using unstructured datasets. People are facing a slew of issues relating to farming, business, and property damage, among many other things, as a result of substantial weather swings. Because of the unpredictability of climatic and atmospheric circumstances, weather forecasting is becoming an increasingly important subject of research. New technology is being developed by scientists. Accurate weather forecasting aids in the avoidance of disasters, the picking of high-yield crops for a given year by farmers, and the preparation of businesses for changing circumstances. With the arrival of the AI and machine learning era, there has been a huge increase in weather research, as well as many models based on these technologies. With the coming of the Artificial Intelligence and Machine Learning era, there is significant growth in weather research. Also many models based on the Artificial Neural Network are developed to predict the accurate weather. These models required a few perplexing mathematical equations. These models study the weather from various aspects and help to get nearly accurate results. In this research we showed the comparison between different models which helps to predict the weather and we tried to figure out which is the best approach to achieve maximum efficiency and compare various parameters of the model like which one will give maximum efficiency, accuracy and data-loss.

References

Sarvesh Landge, Brijesh Kanaujiya, Dr. Sunil M. Wanjari, Aditya Taksande, Rachit Khandelwal, Shienell Amair, “Radar Vision - Weather Forecasting Using CNN-LSTM ” ICCAE2021: International Conference on Computing and Applied Engineering Grand Inn, GOA-INDIA GOA, India, July 23-24, 2021

Nayan Agrawal, Jasneet Kaur saini, Aditya Sharma, Moin Sheikh, Dr. Sunil M. Wanjari “Weather Forecasting: Era of Artificial Intelligence” IRJET2020: International Journal of Engineering and Technology, vol. 07, Issue 04, April , 2020

James W Wilson, N Andrew Crook, Cynthia K Mueller, Juanzhen Sun, and Michael Dixon, “Nowcasting thunderstorms: A status report,” Bulletin of the American Meteorological Society, vol. 79, no. 10, pp. 2079–2100, 1998.

Peter Lynch, “The origins of computer weather prediction and climate modeling,” Journal of Computational Physics, vol. 227, no. 7, pp. 3431–3444, 2008.

Neil I Fox and James W Wilson, “Very short period quantitative precipitation forecasting,” Atmospheric Science Letters, vol. 6, no. 1, pp. 7–11, 2005..

A Bellon and GL Austin, “The accuracy of short-term radar rainfall forecasts,” Journal of hydrology, vol. 70, no. 1-4, pp. 35– 49, 1984

Neill EH Bowler, Clive E Pierce, and Alan Seed, “Development of a precipitation nowcasting algorithm based upon optical flow techniques,” Journal of Hydrology, vol. 288, no. 1-2, pp. 74–91, 2004.

Frank Steinbrücker, Thomas Pock, and Daniel Cremers, “Large displacement optical flow computation withoutwarping,” in 2009 IEEE 12th International Conference on Computer Vision. IEEE, 2009, pp. 1609–1614.

Yu Liu, Du-Gang Xi, Zhao-Liang Li, and Yang Hong, “A new methodology for pixel-quantitative precipitation nowcasting using a pyramid lucas kanade optical flow approach,” Journal of Hydrology, vol. 529, pp. 354–364, 2015.

Till Kroeger, Radu Timofte, Dengxin Dai, and Luc Van Gool, “Fast optical flow using dense inverse search,” in European Conference on Computer Vision. Springer, 2016, pp. 471–488.

Wang-chun Woo and Wai-kin Wong, “Operational application of optical flow techniques to radar-based rainfall nowcasting,” Atmosphere, vol. 8, no. 3, pp. 48, 2017.

Tage Andersson and Karl-Ivar Ivarsson, “A model for probability nowcasts of accumulated precipitation using radar,” Journal of Applied Meteorology, vol. 30, no. 1, pp. 135–141, 1991.

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Published

18-04-2022

How to Cite

Rishi Nandan, Dr. Sunil M. Wanjari, Mr. Brijesh Kanaujiya, Pranjali Meshram, Devyani Adchule, & Punit Sharma. (2022). COMPARING DIFFERENT COLOUR MODELS USED FOR ANALYSIS OF RADAR DATA. International Journal for Research Publication and Seminar, 13(3), 107–111. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/542

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Original Research Article

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