Mapping classifier systems into neural networks
Advances in neural information processing systems 1
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Ants War with Evolutive Pheromone Style Communication
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
Adaptability of Darwinian and Lamarckian Populations toward an Unknown New World
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
SEAL'98 Selected papers from the Second Asia-Pacific Conference on Simulated Evolution and Learning on Simulated Evolution and Learning
Hybrid Computational Intelligence Schemes in Complex Domains: An Extended Review
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
A GA-Based Algorithm with a Very Fast Rate of Convergence
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
Does Crossover Probability Depend on Fitness and Hamming Differences in Genetic Algorithms?
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Multilevel Genetic Algorithm for the Complete Development of ANN
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Proceedings of the Second European Workshop on Genetic Programming
Genetic Algorithms in Machine Learning
Machine Learning and Its Applications, Advanced Lectures
Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
Using the genetic algorithm to build optimal neural networks for fault-prone module detection
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Evolutionary Neural Networks: A Robust Approach to Software Reliability Problems
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
Computational Intelligence: Concepts to Implementations
Computational Intelligence: Concepts to Implementations
A hierarchy of evolution programs: An experimental study
Evolutionary Computation
Modeling the evolution of motivation
Evolutionary Computation
Neural Network Research Progress and Applications in Forecast
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
Expert Systems with Applications: An International Journal
Genetic algorithms and artificial life
Artificial Life
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Using an Evolutionary Neural Network for web intrusion detection
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
Preference learning for cognitive modeling: a case study on entertainment preferences
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Evolutionarily optimized features in functional link neural network for classification
Expert Systems with Applications: An International Journal
Evolving neural networks for decomposable problems using genetic programming
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Discovering several robot behaviors through speciation
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
A Lamarckian Hybrid of Differential Evolution and Conjugate Gradients for Neural Network Training
Neural Processing Letters
A differential evolution based neural network approach to nonlinear system identification
Applied Soft Computing
NN'10/EC'10/FS'10 Proceedings of the 11th WSEAS international conference on nural networks and 11th WSEAS international conference on evolutionary computing and 11th WSEAS international conference on Fuzzy systems
WSEAS TRANSACTIONS on SYSTEMS
Empirical studies on the speed of convergence of neural network training using genetic algorithms
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
The development of a weighted evolving fuzzy neural network
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
An evolutionary neural network approach to intrinsic plagiarism detection
AICS'09 Proceedings of the 20th Irish conference on Artificial intelligence and cognitive science
License plate detection based on genetic neural networks, morphology, and active contours
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Parameter genetic learning of perceptron networks
ICS'06 Proceedings of the 10th WSEAS international conference on Systems
Evolutionary design of constructive multilayer feedforward neural network
ICS'06 Proceedings of the 10th WSEAS international conference on Systems
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Training neural networks with harmony search algorithms for classification problems
Engineering Applications of Artificial Intelligence
Towards capturing and enhancing entertainment in computer games
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
Alternate learning algorithm on multilayer perceptrons
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
Determining regularization parameters for derivative free neural learning
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
Evolutionary computation and its applications in neural and fuzzy systems
Applied Computational Intelligence and Soft Computing
Simultaneous optimization of artificial neural networks for financial forecasting
Applied Intelligence
Advances in Fuzzy Systems - Special issue on Hybrid Biomedical Intelligent Systems
Improving the controllability of tilt interaction for mobile map-based applications
International Journal of Human-Computer Studies
Evolutionary artificial neural networks: a review
Artificial Intelligence Review
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
Applying evolutionary computation to harness passive material properties in robots
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Robust Neuroevolutionary Identification of Nonlinear Nonstationary Objects
Cybernetics and Systems Analysis
International Journal of Hybrid Intelligent Systems
Evolving multilayer feedforward neural network using adaptive particle swarm algorithm
International Journal of Hybrid Intelligent Systems
Hi-index | 0.00 |
Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application to some realworld problems has been hampered by the lack of a training algonthm which reliably finds a nearly globally optimal set of weights in a relatively short time. Genetic algorithms are a class of optimization procedures which are good at exploring a large and complex space in an intelligent way to find values close to the global optimum. Hence, they are well suited to the problem of training feedforward networks. In this paper, we describe a set of experiments performed on data from a sonar image classification problem. These experiments both 1) illustrate the improvements gained by using a genetic algorithm rather than backpropagation and 2) chronicle the evolution of the performance of the genetic algorithm as we added more and more domain-specific knowledge into it.