Multiobjective Optimization in Bioinformatics and Computational Biology
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A memetic model of evolutionary PSO for computational finance applications
Expert Systems with Applications: An International Journal
AG-ART: An adaptive approach to evolving ART architectures
Neurocomputing
Calibrating Probability Density Forecasts with Multi-objective Search
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Robotics and Computer-Integrated Manufacturing
Expert Systems with Applications: An International Journal
"Dead" Chromosomes and Their Elimination in the Neuro-Genetic Stock Index Prediction System
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Applications of multi-objective structure optimization
Neurocomputing
Multiobjective evolutionary neural networks for time series forecasting
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Sensitivity versus accuracy in multiclass problems using memetic Pareto evolutionary neural networks
IEEE Transactions on Neural Networks
Neuro-genetic system for stock index prediction
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Evolutionary neural networks for practical applications
Prediction of commodity prices in rapidly changing environments
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Making good probability estimates for regression
ECML'06 Proceedings of the 17th European conference on Machine Learning
Multi-objective hybrid evolutionary algorithms for radial basis function neural network design
Knowledge-Based Systems
Modular symbiotic adaptive neuro evolution for high dimensionality classificatory problems
Intelligent Decision Technologies
Breast Cancer Diagnosis Using Optimized Attribute Division in Modular Neural Networks
Journal of Information Technology Research
Information Sciences: an International Journal
Evolving multilayer feedforward neural network using adaptive particle swarm algorithm
International Journal of Hybrid Intelligent Systems
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For the purposes of forecasting (or classification) tasks neural networks (NNs) are typically trained with respect to Euclidean distance minimization. This is commonly the case irrespective of any other end user preferences. In a number of situations, most notably time series forecasting, users may have other objectives in addition to Euclidean distance minimization. Recent studies in the NN domain have confronted this problem by propagating a linear sum of errors. However this approach implicitly assumes a priori knowledge of the error surface defined by the problem, which, typically, is not the case. This study constructs a novel methodology for implementing multiobjective optimization within the evolutionary neural network (ENN) domain. This methodology enables the parallel evolution of a population of ENN models which exhibit estimated Pareto optimality with respect to multiple error measures. A new method is derived from this framework, the Pareto evolutionary neural network (Pareto-ENN). The Pareto-ENN evolves a population of models that may be heterogeneous in their topologies inputs and degree of connectivity, and maintains a set of the Pareto optimal ENNs that it discovers. New generalization methods to deal with the unique properties of multiobjective error minimization that are not apparent in the uni-objective case are presented and compared on synthetic data, with a novel method based on bootstrapping of the training data shown to significantly improve generalization ability. Finally experimental evidence is presented in this study demonstrating the general application potential of the framework by generating populations of ENNs for forecasting 37 different international stock indexes.