DICE

The DICE (Disaster Intelligence Initiative) stands as our pioneering research group, launching its endeavours in June 2022. Nestled within the esteemed Department of Mathematics at NIT Agartala, we are at the forefront of utilizing advanced AI methodologies to tackle the myriad challenges faced by individuals and authorities amidst calamities. Our analyses serve as a beacon of insight, offering invaluable contributions to mitigating disaster impacts and fostering proactive planning. With a global network of collaborators, we strive for excellence and standardized results in our mission.

Research Output:

Biswas, S., Kumar, D., Hajiaghaei-Keshteli, M., & Bera, U. K. (2024). An AI-based framework for earthquake relief demand forecasting: A case study in Türkiye. International Journal of Disaster Risk Reduction, 102, 104287. https://doi.org/10.1016/j.ijdrr.2024.104287

2. Biswas, S., Belamkar, P., Sarma, D., Tirkolaee, E. B., & Bera, U. K. (2024). A multi-objective optimization approach for resource allocation and transportation planning in institutional quarantine centres. Annals of Operations Research. https://doi.org/10.1007/s10479-024-06072-8

3. Biswas, S., Kumar, D., Nas, M., Softa, M., Akgun, E., & Bera, U. K. (2024). Performance of a Five-Layer ANN model for earthquake magnitude prediction and spatial risk mapping in Turkey. Decision Making Advances, 3(1), 40–49. https://doi.org/10.31181/dma31202553

4. Biswas, S., Kumar, D., & Bera, U. K. (2024). Testing of Advanced Machine Learning for Flood Forecasting: A Case Study of the Gumti Basin in Tripura, India. In Abstract Id. 214 [Paper & Poster Presentation]. 3rd Roorkee Water Conclave 2024, Indian Institute of Technology Roorkee & National Institute of Hydrology, Roorkee, India. https://www.iitr.ac.in/rwc