Cork scientists’ machine learning tools can predict transport demand

Machine Learning

TrebuNet, a machine learning tool built by Cork scientists, helps governments remove uncertainty from decarbonization plans.

Thanks to research by scientists at University College Cork (UCC), countries around the world will be able to better estimate their future transportation needs.

Transportation-related emissions account for a significant portion of the world’s greenhouse gas emissions, so finding ways to measure and forecast demand can help governments improve climate policy.

UCC academics collaborated with Columbia University scientists on research that led to the creation of a machine learning platform called TrebuNet.

This tool works more efficiently and accurately than current methods that countries use to measure future transport demand.

Historically, forecasting transportation utilization has been done by simulating demand or using regression-based analysis.

UCC academics believe that machine learning architectures can be applied to the broader energy modeling sector.

Siddarth Joshi led this research as part of his PhD in Energy Engineering at UCC. “This study provides insight into the development of new machine learning architectures that improve the accuracy of transport energy service demand estimates,” he said.

“Innovative machine learning architectures and their benefits are measurable for the energy modeling community and transferable across a range of disciplines.”

Brian Ó Gallachóir, a UCC professor of energy engineering, said the new system of forecasting transport demand would not only serve “as a backbone for understanding the future direction of global energy markets,” but also help with climate policy. agreed with

Joshi and his colleagues’ research was published in the Scientific Reports journal. James Glynn, Ph.D., senior fellow at Columbia University, said the new method devised by the researchers demonstrates an innovation in energy system modeling and data analysis to address weaknesses in understanding perspectives within energy system models. I explained that I did.

“This will help remove uncertainty in the decarbonization path,” he added. “Decarbonizing transport in line with the 2050 net-zero goal requires urgent climate change action.Colombia SIPA and UCC collaboration provides decision makers with tools and evidence-based research to design climate policies.” leading to new approaches in energy system modeling and data science to provide

UCC conducts a number of Irish studies related to energy modeling. In February, two of his UCC academics received his €3.5 million funding from the government to find out how energy modeling could help Ireland.

10 things you should know. It arrives straight to your weekday inbox.sign up for daily briefSilicon Republic’s digest of important science and technology news.

Source link

Leave a Reply

Your email address will not be published. Required fields are marked *