True Power Loss Dwindling and Stability Augmentation by Extreme Learning Machine based Hybrid Lepidoptera-Labidognatha Algorithms and Rhinotia Haemoptera Based Hybrid Canis Aureus Girneys Optimization Algorithm

Abstract

In this paper Extreme Learning Machine based Hybrid Lepidoptera-Labidognatha Algorithms and Rhinotia haemoptera based Hybrid Canis aureus and Girneys optimization algorithm has been applied for solving the power loss lessening problem. In Lepidoptera algorithm Location and stage are rationalized in all iteration. The location modernizing procedure is sustained iteratively up until the end norm is satisfied. And in Labidognatha algorithm every Labidognatha in population, subsequent to the capricious walk step, will have diminutive probability to make a decision on not following its current target and bound away from its existing position. A vibration is spread over the web when a Labidognatha shifts to a new-fangled location. Every vibration seizes the information of one Labidognatha and other Labidognatha can get the information in receipt of the vibration. At its current location it creates vibration when Labidognatha moves to a novel position. In this paper Extreme Learning Machine based Hybrid Lepidoptera and Labidognatha Algorithms is designed to solve the problem. Then in this paper Rhinotia haemoptera based hybrid Canis aureus and Girneys optimization algorithm is modelled for solving the problem. In Canis aureus optimization algorithm deeds of the Canis aureus are used to formulate the algorithm. Through stalking, sneaking and jumping on prey, it hunts. Canis aureus optimization algorithm algorithm imitates the behaviour of Canis aureus as Discover and Stalk segment. Girneys algorithm imitate the deeds of the Girneys have been imitated to formulate the algorithm. Dominant male run the subgroups on the periphery of the central group and communicates messages between the peripheral males and the central. In the projected Rhinotia haemoptera based hybrid Canis aureus and Girneys optimization algorithm Portent Canis aureus will control the quarry expanse by the complete pragmatic from earlobes. This exploit is very alike to the doings of Rhinotia haemoptera drive. Then a modernizing strategy which grounded on the cosine function is used to control the process of the algorithm for evading the local optima. Then Girneys movement are included in the hybridized algorithm. Legitimacy of the Extreme Learning Machine based Hybrid Lepidoptera-Labidognatha algorithms and Rhinotia haemoptera based hybrid Canis aureus and Girneys optimization algorithm is substantiated in IEEE 30 bus system (with and devoid of L-index). Actual power loss lessening is reached. Proportion of actual power loss lessening is augmented

Please cite this article as:

Kanagasabai L. True power loss dwindling and stability augmentation by Extreme Learning Machine based Hybrid Lepidoptera-Labidognatha Algorithms and Rhinotia haemoptera based Hybrid Canis Aureus Girneys Optimization algorithm. Herald of the Bauman Moscow State Technical University, Series Natural Sciences, 2023, no. 5 (110), pp. 4--31. DOI: https://doi.org/10.18698/1812-3368-2023-5-4-31

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