This paper proposes a functional link artificial neural network(FLANN) model trained using a modified fish swarm optimization (FSO) algorithm for nonlinear system identification. The system modelling problem has been reformulated as an optimization problem. The FSO algorithm has been modified by incorporating the immunity features of the artificial immune systems. Simulation study reveals improved performance of the proposed algorithm over the conventional FSO algorithm for nonlinear system identification.
KUMAR, RITESH and SAHAY, NISHANT
"NONLINEAR SYSTEM IDENTIFICATION USING A NOVEL IMMUNE ARTIFICIAL FISH SWARM ALGORITHM,"
International Journal of Electronics and Electical Engineering: Vol. 3
, Article 6.
Available at: https://www.interscience.in/ijeee/vol3/iss1/6