Research on electronic power allocation mechanism based on artificial intelligence

Qitong Guo

doi:10.1117/12.3003980

11 October 2023 Research on electronic power allocation mechanism based on artificial intelligence

Qitong Guo

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 1280061 (2023) https://doi.org/10.1117/12.3003980
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

At present, electronic power has become an essential energy source and widely used in manufacturing and social life. Indeed, the utilization electronic power allocation mechanism can avoid the unnecessary waste of energy. However, existing allocation systems are mainly based on the principle of first come and first served or use the matching algorithms for the requester of electronic power, which may cause several unreasonable allocation results. In this work, we initially propose a novel artificial intelligent method to dispose the electric power allocation issue. Subsequently, we utilize the artificial neural network to allocate the electronic power sources by simulating the pair of electronic power supplier and requester and training the mechanism with enough iteration epoch. From our extensive simulation results, we can conclude that our proposed mechanism can successful assign the reasonable electrical sources with reasonable response time costs. We also compare our mechanism with existing electrical power allocation algorithms and evaluate the requester satisfaction ratio as the indicator of model results.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qitong Guo "Research on electronic power allocation mechanism based on artificial intelligence", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 1280061 (11 October 2023); https://doi.org/10.1117/12.3003980

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KEYWORDS

Artificial neural networks

Artificial intelligence

Performance modeling

Education and training

Electronic components

Power supplies

Image processing

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