E-Paper
IIT Mandi scientists develop algorithm to improve landslide prediction accuracy
The developed algorithm has been tested for landslides and can be applied to other natural phenomena such as floods, avalanches, extreme weather events, rock glaciers and permafrost, IIT Mandi said.
Indian Institute of Technology (IIT) Mandi Researchers have developed a new algorithm using artificial intelligence and machine learning (AI&ML) that could improve the accuracy of prediction for natural hazards, the institute said on Tuesday.
Developed by Dr Dericks Praise Shukla, Associate Professor, School of Civil and Environmental Engineering and former research scholar Dr Sharad Kumar Gupta, the algorithm can tackle the challenge of data imbalance for landslide susceptibility mapping which represents the likelihood of landslide occurrences in a given area, it said.
The institute said findings of the research have been published in the journal Landslides.
“The use of Artificial Intelligence (AI) is becoming increasingly vital for the prediction of natural disasters such as landslides. They can potentially predict extreme events, create hazard maps, detect events in real-time, provide situational awareness, and support decision-making. Machine Learning (ML) is a subfield of Artificial Intelligence that enables computers to learn and improve from experience, without being explicitly programmed. It is based on algorithms that can analyse data, identify patterns, and make predictions or decisions, much like human intelligence,” IIT Mandi said in a press statement.
Elaborating on the uniqueness of their work, Dr Shukla said, “This new ML algorithm highlights the importance of data balancing in ML models and demonstrates the potential for new technologies to drive significant advancements in the field. It also underscores the critical need for large amounts of data to accurately train ML models, particularly in the case of geohazards and natural disasters where the stakes are high and human safety is at risk.”
