A computer program that uses artificial intelligence to sort through historical meteorological data is being developed to help predict where and when future forest fires will take place so they can be prevented.
A computer program that uses artificial intelligence to sort through historical meteorological data is being developed to help predict where and when future forest fires will take place so they can be prevented.
University of Alberta wildland fire expert Mike Flannigan, who is also the director of Canada Wildfire, is working with Ryan Lagerquist, a PhD student at the University of Oklahoma’s School of Meteorology, to create the program.
It uses a form of machine learning called an artificial neural network to sort through the data, which is associated with high-intensity wildfires, and predict where extreme weather is most likely to create the conditions for a forest fire.
Researchers feed the system data and it makes predictions based on probability. Then researchers tell the system whether it has made the right decision. If it’s wrong, the system modifies its approach and tries again.
Continue reading at University of Alberta.
Image via University of Alberta.
