WebApr 14, 2024 · Firstly, justification of the proposed algorithm was achieved by benchmarking it on 10 functions and then a comparison of the parameter estimation results obtained using the Hybrid Particle Swarm Optimization Puffer Fish algorithm was done with other meta-heuristic algorithms, i.e., Particle Swarm Optimization, Puffer Fish … WebApr 12, 2024 · In the last few years, various optimization techniques were employed to obtain gains of the PI controller 39, including the Marine Predators Algorithm 40, …
Grey wolf optimization - Introduction - GeeksforGeeks
WebFeb 27, 2024 · The aim of Grey wolf optimization algorithm is to find minimize of fitness function. Fitness Functions: 1) Rastrigin function: Rastrigin function is a non-convex function used as a performance test … WebTherefore, it is necessary to boost the output of the PV system. In this paper, an improved DC-DC SEPIC converter is used for enhancing the PV output, which is further used in … edith arnell moon
Arithmetic optimization algorithm based maximum power point …
WebIn this paper, we have proposed an improved version of the grey wolf optimization (IGWO) algorithm to overcome the premature convergence of conventional GWO algorithm. … WebMar 1, 2014 · Abstract. This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) inspired by grey wolves (Canis lupus). The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership … WebGrey wolf optimizer (GWO) is a population-based meta-heuristics algorithm that simulates the leadership hierarchy and hunting mechanism of grey wolves in nature, and it’s proposed by Seyedali Mirjalili et al. in 2014. Grey wolves are considered apex predators, which are at the top of the food chain. Grey wolves prefer to live in groups (packs ... edith arzberger