Improved segmentation of meristem cells by an automated optimisation algorithm

Author(s):  
O. Rojas ◽  
M.G. Forero ◽  
J.M. Menéndez ◽  
A. Jones ◽  
W. Dewitte ◽  
...  
2021 ◽  
Vol 158 ◽  
pp. S113-S115
Author(s):  
C. Bélanger ◽  
É. Poulin ◽  
S. Aubin ◽  
J.A.M. Cunha ◽  
L. Beaulieu

2017 ◽  
Vol 105 ◽  
pp. 30-47 ◽  
Author(s):  
Shahrzad Saremi ◽  
Seyedali Mirjalili ◽  
Andrew Lewis

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3737
Author(s):  
Mehdi Neshat ◽  
Nataliia Sergiienko ◽  
Seyedali Mirjalili ◽  
Meysam Majidi Nezhad ◽  
Giuseppe Piras ◽  
...  

Ocean renewable wave power is one of the more encouraging inexhaustible energy sources, with the potential to be exploited for nearly 337 GW worldwide. However, compared with other sources of renewables, wave energy technologies have not been fully developed, and the produced energy price is not as competitive as that of wind or solar renewable technologies. In order to commercialise ocean wave technologies, a wide range of optimisation methodologies have been proposed in the last decade. However, evaluations and comparisons of the performance of state-of-the-art bio-inspired optimisation algorithms have not been contemplated for wave energy converters’ optimisation. In this work, we conduct a comprehensive investigation, evaluation and comparison of the optimisation of the geometry, tether angles and power take-off (PTO) settings of a wave energy converter (WEC) using bio-inspired swarm-evolutionary optimisation algorithms based on a sample wave regime at a site in the Mediterranean Sea, in the west of Sicily, Italy. An improved version of a recent optimisation algorithm, called the Moth–Flame Optimiser (MFO), is also proposed for this application area. The results demonstrated that the proposed MFO can outperform other optimisation methods in maximising the total power harnessed from a WEC.


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