Widi Aribowo, Bambang Suprianto, I Gusti Putu Asto Buditjahjanto, Mahendra Widyartono, Miftahur Rohman
The parasitism – predation algorithm (PPA) is an optimization method that duplicates the in-teraction of mutualism between predators (cats), parasites (cuckoos), and hosts (crows). The study employs a combination of the PPA methods using the cascade-forward backpropagation neural network. This hybrid method employs an automatic voltage regulator (AVR) on a single machine system, with the performance measurement focusing on speed and the rotor angle. The performance of the proposed method is compared with the feed-forward backpropagation neural network (FFBNN), cascade-forward backprop-agation neural network (CFBNN), Elman recurrent neural network (E-RNN), focused time-delay neural network (FTDNN), and distributed time-delay neural network (DTDNN). The results show that the proposed method exhibits the best speed and rotor angle performance. The PPA-CFBNN method has the ability to reduce the overshoot of the speed by 1.569% and the rotor angle by 0.724%. © 2021 Author(s).
Department of Electrical Engineering, Universitas Negeri Surabaya, Indonesia
