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

… in a diversity of predators. In this study, the confusion effect is investigated using a simple
artificial neural network model consisting of a sensory surface, a neural bottleneck (commonly …

… between predictions of neural network models and experimental … neural network models.
In the final experiment, we test whether density, area, and/or number have effects on predator …

… have proposed artificial neural networks (ANNs) prediction models for Brazil and … neural
network (MLPNN) in conjunction with a prey predator algorithm (PPA). The two proposed model …

… novel swarm intelligence algorithm, ie the marine predator algorithm (MPA). In the proposed
… neural networks. After training, the hybrid feedforward neural networks and marine predator …

… Here we present a CNN model for classification of non… models based on modified version
of Marine Predators algorithm (MPA) and CNN, known as the IMPA-CNN. The proposed model …

… solver with Morlet wavelet neural networks (MW-NNs) is presented for solving the mathematical
predator–prey model by exploiting the strength of MW-NNs modeling, optimization ability …

… , ie, Elman Recurrent Neural Network (ERNN) and back-propagation and found the
hybrid ML model with ERNN to achieve better prediction accuracy than the model with back-…

… mechanism through artificial neural networks, genetic algorithms and … neural network based
differential equation models of the system are constructed and optimization of the networks …

… predatory chat conversations in large volumes of chat logs. We present a classifier based on
Convolutional Neural Network … Machine (SVM) and regular Neural Network (NN) in terms of …