Evolutionary artificial neural networks: a review

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Genetic CNN (2017, background): “Efforts are also made to add invariance into the network structure [38].”
Multiobjective optimization for empty and foam-filled square columns under oblique impact loading (2013, background): “The polynomial response surface (PRS) models [45], moving least square (MLS) [46], Kriging [47] and artificial neural network (ANN) [48] are some of the most commonly adopted metamodels.”
An Optimization Spiking Neural P System for Approximately Solving Combinatorial Optimization Problems (2014, background): “Inspired by the central nervous systems of animals, artificial neural networks (ANNs) in computer science and related fields refer to a class of computational models consisting of interconnected neurons.(15,18) ANNs are capable of machine learning and pattern recognition through computing values fro”
Human action recognition using genetic algorithms and convolutional neural networks (2016, methodology): “In the literature, genetic algorithms (GA) were used to optimize neural network systems by feature selection [44,45], topology selection [46,47], weight selection [48,49].”