Glasgow Researchers Utilize Machine Learning to Create Digital Replica of Network
| Source: Computer Weekly | Original article
Glasgow researchers leverage machine learning to create a digital twin of complex networks. This innovation saves hours compared to traditional testing methods.
Researchers at the University of Glasgow have successfully utilized machine learning to build a digital twin of complex networks, significantly reducing the time required for traditional network testing. This breakthrough is part of a broader effort to leverage digital twins in various sectors, including transport and manufacturing, to drive efficiency and decarbonization.
As we reported on May 6, 2026, in the context of the 2026 Roadmap on Artificial Intelligence and Machine Learning for Smart Manufacturing, digital twins are increasingly being recognized for their potential to transform industries. The Glasgow researchers' use of automated machine learning (AutoML) to build digital twins of networks is a notable advancement, as it not only accelerates the process but also enhances accuracy.
What matters here is the potential for widespread adoption of digital twins across different sectors, from transport to semiconductor manufacturing, as seen in initiatives like Smart USA. The University of Glasgow's involvement in a £46m digital twin hub for transport and its own Smart Campus Initiative underscores the institution's commitment to this technology. As digital twins continue to gain traction, we can expect to see more innovative applications and collaborations, particularly in the context of net-zero initiatives and smart manufacturing.
Sources
Back to AIPULSEN