A hybrid mutational Northern Goshawk and elite opposition learning artificial rabbits optimizer for PEMFC parameter estimation
Abstract For the purpose of simulating, controlling, evaluating, managing and optimizing PEMFCs it is necessary to develop accurate mathematical models. The present study develops a mathematical model which uses empirical or semi-empirical equations to estimate unknown model parameters through optim...
        Saved in:
      
    
          | Main Authors: | Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah | 
|---|---|
| Format: | Article | 
| Language: | English | 
| Published: | Nature Portfolio
    
        2024-11-01 | 
| Series: | Scientific Reports | 
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-80073-2 | 
| Tags: | Add Tag 
      No Tags, Be the first to tag this record!
   | 
Similar Items
- 
                
                    A levy chaotic horizontal vertical crossover based artificial hummingbird algorithm for precise PEMFC parameter estimation        
                          
 by: Pradeep Jangir, et al.
 Published: (2024-11-01)
- 
                
                    Precision parameter estimation in Proton Exchange Membrane Fuel Cells using depth information enhanced Differential Evolution        
                          
 by: Pradeep Jangir, et al.
 Published: (2024-11-01)
- 
                
                    The quick crisscross sine cosine algorithm for optimal FACTS placement in uncertain wind integrated scenario based power systems        
                          
 by: Sunilkumar P. Agrawal, et al.
 Published: (2025-03-01)
- 
                
                    MORKO: A Multi-objective Runge–Kutta Optimizer for Multi-domain Optimization Problems        
                          
 by: Kanak Kalita, et al.
 Published: (2025-01-01)
- 
                
                    Innovative Diversity Metrics in Hierarchical Population‐Based Differential Evolution for PEM Fuel Cell Parameter Optimization        
                          
 by: Mohammad Khishe, et al.
 Published: (2025-01-01)
 
       