The cascade-correlation learning architecture
Advances in neural information processing systems 2
Designing application-specific neural networks using the genetic algorithm
Advances in neural information processing systems 2
Advances in neural information processing systems 2
Neural network constructive algorithms: trading generalization for learning efficiency?
Circuits, Systems, and Signal Processing - Special issue: networks for neural processing
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Evolving Multilayer Perceptrons
Neural Processing Letters
Cooperative-Competitive Algorithms for Evolutionary Networks Classifying Noisy Digital Images
Neural Processing Letters
Neural Networks for Identification, Prediction, and Control
Neural Networks for Identification, Prediction, and Control
Designing Neural Networks using Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Topology Design of Feedforward Neural Networks by Genetic Algorithms
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Balancing Learning And Evolution
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
EP '97 Proceedings of the 6th International Conference on Evolutionary Programming VI
Active guidance for a finless rocket using neuroevolution
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
A new evolutionary system for evolving artificial neural networks
IEEE Transactions on Neural Networks
Constructive neural-network learning algorithms for pattern classification
IEEE Transactions on Neural Networks
Learning polynomial feedforward neural networks by genetic programming and backpropagation
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
An evolutionary algorithm that constructs recurrent neural networks
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
Training neural networks with harmony search algorithms for classification problems
Engineering Applications of Artificial Intelligence
A hybrid algorithm for artificial neural network training
Engineering Applications of Artificial Intelligence
Performance analysis of colour descriptors for parquet sorting
Expert Systems with Applications: An International Journal
Fuzzy logic-based pre-classifier for tropical wood species recognition system
Machine Vision and Applications
A sequential machine vision procedure for assessing paper impurities
Computers in Industry
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This study addresses the design and the training of a Multi-Layer Perceptron classifier for identification of wood veneer defects from statistical features of wood sub-images. Previous research utilised a neural network structure manually optimised using the Taguchi method with the connection weights trained using the Backpropagation rule. The proposed approach uses the evolutionary Artificial Neural Network Generation and Training (ANNGaT) algorithm to generate the neural network system. The algorithm evolves simultaneously the neural network topology and the weights. ANNGaT optimises the size of the hidden layer(s) of the neural network structure through genetic mutations of the individuals. The number of hidden layers is a system parameter. Experimental tests show that ANNGaT produces highly compact neural network structures capable of accurate and robust learning. The tests show no differences in accuracy between neural network architectures using one and two hidden layers of processing units. Compared to the manual approach, the evolutionary algorithm generates equally performing solutions using considerably smaller architectures. Moreover, the proposed algorithm requires a lower design effort since the process is fully automated.