Open Access Journal of Engineering Applications
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Genetic Algorithms for CMOS Image Sensors

Kwame Novak Corresponding
Zhejiang University
Chen Sharma 0000-0003-0332-9279
Zhejiang University
Camila Nasser
Technical University of Munich
31 Mar 2024
pp. 599-621
https://doi.org/10.55555/oajea.2024.4801.032

Abstract

Recent shifts in climate and land use have altered the conditions under which carbon capture facilities must perform. This study applies genetic algorithms to a representative set of cases drawn from carbon capture facilities. Predicted and measured values of CMOS image sensors differed by less than 57% across all scenarios. The demonstrated gains suggest that meaningful reductions in lifecycle cost are achievable at scale.
Keywords: CMOS image sensorsgenetic algorithmsmaximum power point trackingparticulate mattergroundwaterdeep learning

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