Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Multidimensional data clustering utilizing hybrid search strategies
Pattern Recognition
Developing neural-network applications
AI Expert
Proceedings of the third international conference on Genetic algorithms
Towards the genetic synthesis of neural network
Proceedings of the third international conference on Genetic algorithms
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Neurocomputing: foundations of research
Algorithms for better representation and faster learning in radial basis function networks
Advances in neural information processing systems 2
A resource-allocating network for function interpolation
Neural Computation
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Neural networks and the bias/variance dilemma
Neural Computation
C4.5: programs for machine learning
C4.5: programs for machine learning
Comparative evaluation of genetic algorithm and backpropagation for training neural networks
Information Sciences—Informatics and Computer Science: An International Journal
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
The New Science of Management Decision
The New Science of Management Decision
Genetic Algorithms
Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real World Performance
Learning Logical Definitions from Relations
Machine Learning
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
Using a Neutral Network to Learn General Knowledge in a Case-Based System
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Selected Papers from AISB Workshop on Evolutionary Computing
Evolutionary Design of MLP Neural Network Architectures
SBRN '97 Proceedings of the 4th Brazilian Symposium on Neural Networks (SBRN '97)
Credit Analysis Using Radial Basis Function Networks
ICCIMA '99 Proceedings of the 3rd International Conference on Computational Intelligence and Multimedia Applications
Credit Assessment Using Constructive Neural Networks
ICCIMA '99 Proceedings of the 3rd International Conference on Computational Intelligence and Multimedia Applications
Regularization in the selection of radial basis function centers
Neural Computation
IEEE Transactions on Neural Networks
Decision trees can initialize radial-basis function networks
IEEE Transactions on Neural Networks
Bankruptcy prediction for credit risk using neural networks: A survey and new results
IEEE Transactions on Neural Networks
Optimal adaptive k-means algorithm with dynamic adjustment of learning rate
IEEE Transactions on Neural Networks
Steady-state performance constraints for dynamical models based on RBF networks
Engineering Applications of Artificial Intelligence
A Preliminar Analysis of CO2RBFN in Imbalanced Problems
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
A survey of evolutionary algorithms for clustering
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets
Pattern Recognition Letters
Simultaneous optimization of artificial neural networks for financial forecasting
Applied Intelligence
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Credit analysts generally assess the risk of credit applications based on their previous experience. They frequently employ quantitative methods to this end. Among the methods used, Artificial Neural Networks have been particularly successful and have been incorporated into several computational tools. However, the design of efficient Artificial Neural Networks is largely affected by the definition of adequate values for their free parameters. This article discusses a new approach to the design of a particular Artificial Neural Networks model, RBF networks, through Genetic Algorithms. It presents an overall view of the problems involved and the different approaches employed to optimize Artificial Neural Networks genetically. For such, several methods proposed in the literature for optimizing RBF networks using Genetic Algorithms are discussed. Finally, the model proposed by the authors is described and experimental results using this model for a credit risk assessment problem are presented.