ENHANCED EQUUS FERUS PRZEWALSKII OPTIMIZATION AND ADVANCED OSTEOLAEMUS SEARCH ALGORITHM
DOI:
https://doi.org/10.55766/sujst8562Keywords:
Anarchias Seychellensis, Cryptoprocta, Equus Ferus Przewalskii, Osteolaemus, Peacock HindAbstract
We apply the enhanced Equus Ferus Przewalskii optimization (EEPO) algorithm and the advanced Osteolaemus search optimization (AOSO) algorithm to solve true power loss reduction problems. Equus Ferus Przewalskii tends to pursue and run in its environment. As a result, the adult Equus Ferus Przewalskii and steeds adopt an arbitrary course. At that juncture, a vibrant inertia weight approach is presented to the oasis, and the results will be valuable to poise the exploration and exploitation. The Equus Ferus Przewalskii optimization algorithm is combined with the Anarchias seychellensis and Peacock hind’s teamwork-based optimization algorithm to improve the exploration ability of the process. The Osteolaemus search optimization algorithm imitates the two key phases of Osteolaemus behavior-ringing and stalking. Osteolaemus have flawless nocturnal vision and are primarily nocturnal stalkers. Osteolaemus employ the paleness of victim animals for their sustenance. Osteolaemus are ensnaring slayers, searching for nearby fish or terrestrial animals before proceeding to their next meal. Osteolaemus can track prey over short distances, even out of aquatic conditions. Osteolaemus have double passages in the course of the ringing; tall marching and tummy marching. The osteolaemus search optimization algorithm has assimilated the advanced features of the cryptoprocta search optimization algorithm. This assimilation will upgrade the exploitation competence of the process substantially. The Enhanced Equus Ferus Przewalskii optimization (EEPO) algorithm and the advanced Osteolaemus search optimization (AOSO) algorithm have been tested successfully on 7 standard functions, as well as the IEEE 30, 57, and 118 bus systems, and the Grid 220 kV system.
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