… of neural networks (having the hyperbolic tangent or the logistic sigmoid as activation function)
into predator–… Such a Lotka–Volterra representation of neural networks is of interest for …

… wavelet neural networks (MW-NNs) is presented for solving the mathematical predator–prey …
outcomes as a start point or initial weights for Case 1 of the nonlinear predator–prey model. …

… for evaluation of dynamics of nonlinear prey–predator mathematical model by … neural
networks, genetic algorithms and interior-point algorithm. In the scheme, artificial neural network …

… Gudermannian neural networks (GNNs) for the nonlinear dynamics of prey-predator system
(… -interquartile ranges have been performed for both predator and prey dynamics of the model…

… The purpose of this work is to handle numerically the NBPPS using the supervised
neural networks (SNNs) along with the Levenberg–Marquardt backpropagation approach (LMBA). …

… feed-forward artificial neural network (FFNN) is trained using the marine predators algorithm
(MPA), … Identification/modeling of nonlinear systems is chosen as the problem. Six nonlinear …

… -based fractional order nonlinear prey-predator system using the stochastic procedures of
the scaled conjugate gradient and the artificial neuron networks. The stochastic computational …

… study for the nonlinear host-vector-predator system. The obtained values through the LMBNNs
to solve each class of the nonlinear host-vector-predator system are provided in Figure 3. …

… chain nonlinear … predator Y together with prey of a top-predator Z. The features of prey X
along with the species Y present the modeling of Volterra scheme, which indicates the predator …

… nonlinear problem, and it faces new challenges in model establishment. Artificial neural
networks are widely used in predicting nonlinear time … in the neural network by passing errors. …