Unveiling Cosmic Enigmas: Fast Radio Bursts Analysis Using Machine Learning and Convolutional Neural Networks


  • Vandana Jagtap Shri Venkateswara University, Gajraula, Amroha, Uttar Pradesh, India.
  • Rakesh K. Yadav Dr. Vishwanath Karad world peace University, Pune 411038, India.


Fast Radio Burst, Deep Learning, Machine Learning, Space Telescope, Convolutional Neural Network, Neural Network, Random Forest, Radio Frequency Interference, Transfer Learning, Computer Vision, Incremental Learning, LogReg, Decision Tree, Extra-Tree, Random ForestLGBM


Universe has many mysteries like Pulsars, dying stars, supernovae, and fast radio bursts (FRB) are known as astronomical phenomena or events, which can be recognized by using different ML and DL approaches. Here one of the mysteries of fast radio busts events was discovered by using machine learning and convolution neural network with published data from the voyager radio telescope at frequencies from 8418.457MHz to 8421.38671 MHz. Also the analysis of different algorithm like CNN, LogReg, Decision Tree, Extra-Tree, Random Forest and LGBM to recognized radio emit from miscellaneous light across the electromagnetic spectrum and due to remonstrance advances in radio astronomy, the study of emitted objects in radio waves is the biggest scope of the study, which will be helping us to reveal the mysteries of the Universe.


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How to Cite

Jagtap, V. ., & Yadav, R. K. (2023). Unveiling Cosmic Enigmas: Fast Radio Bursts Analysis Using Machine Learning and Convolutional Neural Networks. International Journal of Intelligent Systems and Applications in Engineering, 12(2s), 93–108. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3562



Research Article