Computer Methods and Programs in Biomedicine
Application of Kohonen network for automatic point correspondence in 2D medical images
Computers in Biology and Medicine
Self-organizing potential field network: a new optimization algorithm
IEEE Transactions on Neural Networks
A computational intelligence scheme for the prediction of the daily peak load
Applied Soft Computing
Multimodal feedforward self-organizing maps
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Evolutionary computation and its applications in neural and fuzzy systems
Applied Computational Intelligence and Soft Computing
International Journal of Swarm Intelligence Research
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Given some optimization problem and a series of typically expensive trials of solution candidates sampled from a search space, how can we efficiently select the next candidate? We address this fundamental problem by embedding simple optimization strategies in learning algorithms inspired by Kohonen's self-organizing maps and neural gas networks. Our adaptive nets or grids are used to identify and exploit search space regions that maximize the probability of generating points closer to the optima. Net nodes are attracted by candidates that lead to improved evaluations, thus, quickly biasing the active data selection process toward promising regions, without loss of ability to escape from local optima. On standard benchmark functions, our techniques perform more reliably than the widely used covariance matrix adaptation evolution strategy. The proposed algorithm is also applied to the problem of drag reduction in a flow past an actively controlled circular cylinder, leading to unprecedented drag reduction.