A novel hybrid krill herd algorithm for modeling solid oxide fuel cells | Zendy

Caiyun Xu | Zendy; Yongsheng Zhou | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A novel hybrid krill herd algorithm for modeling solid oxide fuel cells

Author(s) -

Caiyun Xu,

Yongsheng Zhou

Publication year - 2021

Publication title -

iop conference series earth and environmental science

Language(s) - English

Resource type - Journals

eISSN - 1755-1307

pISSN - 1755-1315

DOI - 10.1088/1755-1315/804/3/032010

Subject(s) - swarm behaviour , computer science , solid oxide fuel cell , krill , optimization algorithm , algorithm , process engineering , mathematical optimization , environmental science , engineering , mathematics , ecology , artificial intelligence , chemistry , electrode , anode , biology

Solid oxide fuel cells are globally recognized as a very promising technology in the area of highly efficient electricity generation with a low environmental impact. In this paper, a novel hybrid krill herd algorithm (nhKHA) is proposed for modeling the solid oxide fuel cells (SOFCs). In nhKHA, the operation inspired by the foraging behavior of fish-swarm is adopted to improve the global search ability, and the operation inspired by the virus search is used to improve the search efficiency and accuracy. The nhKHA is applied to optimize the parameters of the SOFC, the experiment results show that this nhKHA can achieve more higher precision between mathematical model and experimental data compared with some other optimization algorithms.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research