• Deeksha Gupta
• Deepti Sharda
• Navdeep Kaur
• Ritika Bansal

Solar flare is the most crucial space weather phenomena where a sudden burst of radiation and charged elements can affect the working behavior of satellites, power grids and communication system on Earth adversely. The accurate and timely prediction of solar flares allows government and industries to take preventive actions. The complex and non-linear behavior of the solar magnetic fields make the forecasting of solar flare a challenging task. This study aims to review the evolution of artificial intelligence (AI) based data-driven approaches in flare prediction task. This endeavor covers different AI approaches ranging across machine learning (ML) and deep learning (DL) methods for flare prediction, categorizing approaches into classical ML, neural networks, and hybrid models. The study also provides insights into key challenges and outlines the future directions in the field of AI-based flare forecasting research.

Solar flare forecasting, space weather, machine learning; deep learning, predictive models

"ARTIFICIAL INTELLIGENCE IN SOLAR FLARE PREDICTION: PROGRESS, CHALLENGES, AND FUTURE DIRECTIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 9, page no.1-7, September-2026, Available :http://www.jetir.org/papers/JETIRHX06001.pdf

"ARTIFICIAL INTELLIGENCE IN SOLAR FLARE PREDICTION: PROGRESS, CHALLENGES, AND FUTURE DIRECTIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 9, page no. pp1-7, September-2026, Available at : http://www.jetir.org/papers/JETIRHX06001.pdf