01 / MOTIVATION
Why this work matters
Forecasting lockdown decisions requires recognizing patterns in public-health and social-context data.
An artificial-neural-network approach to predicting lockdown timing from epidemiological and socioeconomic signals.
02 / METHODOLOGY
Research approach
The study investigates artificial neural networks for estimating future lockdown timing.
03 / CONTRIBUTIONS
Main contribution
A neural-network model for future lockdown prediction.
Consult the complete publication for numerical findings and experimental qualifications.
04 / PUBLICATION
Read the paper
Shuvra Smaran Das, Anirban Saha Anik, Md. Muzakker Hossain, Md. Kishor Morol, Fariha Jahan, and Md. Abdullah Al-Jubair. (2023). A Study on Future Lockdown Predictions Using ANN. 2023 International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM). https://doi.org/10.1109/NCIM59001.2023.10212686