Run_scripts.py controls the general optimization parameters (Population size, number of runs, number of iterations) Optimizers contains the algorithms of GWO (original from EvoloPy package), and AGWO.

Abstract: Reliable tracking of the plume by the robot is the key to achieving plume source localization. To address the problem of low success rate and long search time of robot source location due to ...

Abstract: A partial shading condition (PSC) is one of the most common problems in the photovoltaic (PV) system. It causes the output power of a PV system drastically decrease. Meta-heuristic ...

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...

The proposed MWA is compared against five existing MPPT algorithms—incremental conductance (INC), perturbation and observation (P&O), particle swarm optimization (PSO), grey wolf optimization (GWO), ...

Metaheuristic optimization algorithms, including Particle Swarm Optimization (PSO), Differential Evolution (DE), and Gray Wolf Optimization (GWO), converged to similar optimum processing conditions, ...

Detector-Evasive LLM Paraphrasing via Constrained Policy Optimization Mingyi Wang, Zhuoer Shen, Yuheng Bu, Shaofeng Zou Detect Before You Leap: Mirage Detection in Vision-Language Models Sayeed ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...