16 papers · ranked by Valyu relevance
Luke Wolfenden, Katarzyna Bolsewicz, Alice Grady, Sam McCrabb + 25 more
'Melanie Kingsland' 'John Wiggers' 'Adrian Bauman' 'Rebecca Wyse' 'Nicole Nathan' 'Rachel Sutherland' 'Rebecca Kate Hodder' 'Maria Fernandez' 'Cara Lewis' 'Natalie Taylor' 'Heather McKay' 'Jeremy Grimshaw' 'Alix Hall' 'Joanna Moullin' 'Bianca Albers' 'Samantha Batchelor' 'John Attia' 'Andrew Milat' 'Andrew Bailey'…
Mojtaba Ghasemi, Abolfazl Rahimnejad, Ebrahim Akbari, Ravipudi Venkata Rao + 4 more
'Ravipudi Venkata Rao' 'Pavel Trojovský' 'Eva Trojovská' 'Stephen Andrew Gadsden' 'Yilun Shang'] Many important engineering optimization problems require a strong and simple optimization algorithm to achieve the best solutions. In 2020, Rao introduced three non-parametric algorithms, known as Rao algorithms, which have…
Olga Speck, Thomas Speck, Sabine Baur, Michael Herdy + 3 more
'Laith Abualigah' 'Xuewen Xia'] With a focus on education and teaching, we provide general background information on bioinspired optimization methods by comparing the concept of optimization and the search for an optimum in engineering and biology. We introduce both the principles of Darwinian evolution and the basic…
David Palma-Heredia, Marta Verdaguer, Vicenç Puig, Manuel Poch + 2 more
'Miquel Àngel Cugueró-Escofet' 'Ernest W. Tollner'] Anaerobic digestion (AnD) is a process that allows the conversion of organic waste into a source of energy such as biogas, introducing sustainability and circular economy in waste treatment. AnD is an intricate process because of multiple parameters involved, and its…
Sam McCrabb, Kaitlin Mooney, Benjamin Elton, Alice Grady + 2 more
'Sze Lin Yoong' 'Luke Wolfenden'] Background Optimisation processes have the potential to rapidly improve the impact of health interventions. Optimisation can be defined as a deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public…
Erin Nolan, Luke Wolfenden, Taylor Benn, Elizabeth Holliday + 3 more
'Daniel Barker' 'Christopher Oldmeadow' 'Alix Hall'] Background Optimisation is the iterative process to improve a health intervention or implementation strategy within resource constraints. This review aimed to identify which study designs are being used to evaluate the optimisation of health interventions and…
Matt J. Owen, Gary R. Mirams, Frédéric E. Theunissen
Ion channel models present many challenging optimisation problems. These include unidentifiable parameters, noisy data, unobserved states, and a combination of both fast and slow timescales. This can make it difficult to choose a suitable optimisation routine a priori. Nevertheless, many attempts have been made to…
Na Zhang, Ziwei Jiang, Gang Hu, Abdelazim G. Hussien + 1 more
Attraction-Repulsion Optimisation Algorithm (AROA) is a newly proposed metaheuristic algorithm for solving global optimisation problems, which simulates the equilibrium relating to the attraction and repulsion phenomenon that occurs in the natural world, and aims to achieve a good balance between the development…
Mohammad Dehghani, Pavel Trojovský, Stuart Burgess
This article introduces a new metaheuristic algorithm called the Serval Optimization Algorithm (SOA), which imitates the natural behavior of serval in nature. The fundamental inspiration of SOA is the serval’s hunting strategy, which attacks the selected prey and then hunts the prey in a chasing process. The steps of…
E. A. Baltz, E. Trask, M. Binderbauer, M. Dikovsky + 4 more
'R. Mendoza' 'J. C. Platt' 'P. F. Riley'] Many fields of basic and applied science require efficiently exploring complex systems with high dimensionality. An example of such a challenge is optimising the performance of plasma fusion experiments. The highly-nonlinear and temporally-varying interaction between the…
Zihuan Zhang, Zao Li, Zhe Guo
In the field of digital design, a recent hot topic is the study of the interaction between spatial environment design and human factors. Electroencephalogram (EEG) and eye tracking can be used as quantitative analysis methods for architectural space evaluation; however, conclusions from existing studies on improving…
Achim Langenbucher, Nóra Szentmáry, Alan Cayless, Jascha Wendelstein + 2 more
In this context, formula constants were optimised for statistical metrics of the SEQ prediction error PE. For the statistical metrics we used: the sum of squared PE (SoSPE) which minimises the ‘energy’ of the prediction error, the sum of the absolute PE (SoAPE, as typically used in scientific reports on the performance…
Julien Diot, Hiroyoshi Iwata
Introduction Advances in genotyping technologies have provided breeders with access to the genotypic values of several thousand genetic markers in their breeding materials. Combined with phenotypic data, this information facilitates genomic selection. Although genomic selection can benefit breeders, it does not…
Gökhan Karaova, Aşkın Altınoklu, Özgür Ergül
A multigrid optimisation strategy is introduced to design passive metallic reflectors with corrugated shapes. The strategy is based on using genetic algorithms at multiple grids and shaping the metal sheets, starting from coarse details to fine tunings. This corresponds to a systematic expansion of the related…
Junxian Chen, Jianhai Zhang, Hongwei Zhao, Ana González-Marcos
Stress uniformity within the gauge zone of a cruciform specimen significantly affects materials’ in-plane biaxial mechanical properties in material testing. The stress uniformity depends on the load transmission of the cruciform specimen from the fixtures to the gauge zone. Previous studies failed to alter the nature…
Shunshun Zhong, Cong Xu, Dongmei Sun, Lian Duan + 3 more
'Zichuan Yi' 'Qiang Xu'] A chaotic adaptive seeker optimization algorithm (CASOA) is proposed in this study to improve the coupling efficiency and accuracy of a butterfly optical communication laser. It primarily relies on chaotic disturbance to improve seeker search performance. The chaotic disturbance enables the…