In this paper, a novel swarm‐based metaheuristic algorithm is proposed, which is called
tuna swarm optimization (TSO). The main inspiration for TSO is based on the cooperative …

The application of artificial intelligence in everyday life is becoming all-pervasive and
unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired …

Recently, many metaheuristic optimization algorithms have been developed to address real-
world issues. In this study, a new physics-based metaheuristic called Fick's law optimization …

Given the photovoltaic (PV) model's multi-model and nonlinear properties, extracting its
parameters is a difficult problem to solve. Furthermore, because of the features of the …

This paper proposes an advanced intelligent application of Enhanced Artificial Gorilla
Troops (EAGT) optimizer for parameters extraction of three different PV modules. The …

The performance of photovoltaic (PV) cell is affected by the model structure and
corresponding parameters. However, these parameters are adjustable and variable, which …

Estimating parameters and establishing high-accuracy and high-reliability models of
photovoltaic (PV) modules by using the actual current-voltage data is important to simulate …

Solar Photovoltaic (SPV) technology advancements are primarily aimed at decarbonizing
and enhancing the resiliency of the energy grid. Incorporating SPV is one of the ways to …

Slime mould algorithm (SMA) is a population‐based metaheuristic algorithm inspired by the
phenomenon of slime mould oscillation. The SMA is competitive compared to other …

The optimal operation of solar cells depends on the accurate determination of parameters in
the Photovoltaic (PV) models, such as resistance and currents, which may vary due to …