Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives. By emulating natural ...

Over the last decade, the field of nanophotonics (or nano-optics) has been developing rapidly, mainly driven by plasmonics, because noble metal nanoparticles allow plasmon resonances to be spectrally ...

Neural network pruning is a key technique for deploying artificial intelligence (AI) models based on deep neural networks (DNNs) on resource-constrained platforms, such as mobile devices. However, ...

This research explores how user-defined constraints affect the efficiency and effectiveness of multi-objective evolutionary algorithm (MOEA) optimization in water resources. Constraints in MOEA ...

Resident data scientist Dr. James McCaffrey of Microsoft Research turns his attention to evolutionary optimization, using a full code download, screenshots and graphics to explain this machine ...

Iryna Yevseyeva is an Associate Professor in Computer Science at the Faculty of Computing, Engineering and Media, School of Computer Science and Informatics. She is Subject Group Leader for Cyber ...

In space engineering, electronic component layout has a very important impact on the centroid stability and heat dissipation of devices. However, the diversity of components, a variety of spatial ...

The urban low-altitude logistics network adopts a hub-and-spoke, multi-layered structure. Its nodes are waypoints mapped to corresponding altitude layers based on spoke nodes (delivery spots) and hub ...

Evolutionary optimization is a technique that can be used to train many types of machine learning models. Evolutionary optimization loosely models the biological processes of natural selection, ...