Document Type : Original Article
Authors
- Antonella Pasternak ^{} ^{1}
- Charis Bresser ^{} ^{2}
^{1} College of Engineering, University of Miami, Coral Gables, FL 33146, USA
^{2} Department of Electrical Engineering, University of North Texas, USA
Abstract
A new Blackbox technique has been presented in the current paper for model estimation of the solid oxide fuel cells (SOFCs) for providing better results. The proposed method is based on a Hierarchical Radial Basis Function (HRBF). The presented method is then developed by a new modified metaheuristic, called Developed Coronavirus Herd Immunity Algorithm. The suggested model has been named DCHIA-HRBF. The proposed model is then trained by some data and prepared for the identification and prediction. The model is then analyzed and were put in comparison with several latest techniques for validation of the efficiency of the technique. It is also verified by the empirical data to prove its validation with the real data. Simulation results specified that the suggested DCHIA-HRBF delivers high effectiveness as an identifier and prediction tool for the SOFCs.
Keywords
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