C4.5: programs for machine learning
C4.5: programs for machine learning
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Machine Learning - Special issue on learning with probabilistic representations
Evolving Multilayer Perceptrons
Neural Processing Letters
A Memetic Pareto Evolutionary Approach to Artificial Neural Networks
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Using the particle swarm optimization technique to train a recurrent neural model
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Evolutionary ensembles with negative correlation learning
IEEE Transactions on Evolutionary Computation
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
A hybrid of genetic algorithm and particle swarm optimization for recurrent network design
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A new evolutionary system for evolving artificial neural networks
IEEE Transactions on Neural Networks
Design of artificial neural networks using a modified particle swarm optimization algorithm
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
PSO-based cloning template design for CNN associative memories
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
Design of artificial neural networks using differential evolution algorithm
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Learning in the feed-forward random neural network: A critical review
Performance Evaluation
Training spiking neurons by means of particle swarm optimization
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
An improved swarm optimized functional link artificial neural network (ISO-FLANN) for classification
Journal of Systems and Software
Evolving multilayer feedforward neural network using adaptive particle swarm algorithm
International Journal of Hybrid Intelligent Systems
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This paper presents a new evolutionary artificial neural network (ANN) algorithm named IPSONet that is based on an improved particle swarm optimization (PSO). The improved PSO employs parameter automation strategy, velocity resetting, and crossover and mutations to significantly improve the performance of the original PSO algorithm in global search and fine-tuning of the solutions. IPSONet uses the improved PSO to address the design problem of feedforward ANN. Unlike most previous studies on only using PSO to evolve weights of ANNs, this study puts its emphasis on using the improved PSO to evolve simultaneously structure and weights of ANNs by a specific individual representation and evolutionary scheme. The performance of IPSONet has been evaluated on several benchmarks. The results demonstrate that IPSONet can produce compact ANNs with good generalization ability.