Lambros Skarlas

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In this contribution, a generic applied evolutionary hybrid technique that combines the effectiveness of adaptive multimodel partitioning filters and genetic algorithm (GAs) robustness has been designed, developed, and applied in real-world adaptive system modeling and information mining problems. The method can be applied to linear and nonlinear real-world(More)
Ab initio coding potential prediction in a bacterial genome is an important step in determining an organism's transcriptional regulatory function. Extensive studies of genes structure have been carried out in a few species such as Escherichia coli, fewer resources exist in newly sequenced genomes like Wolbachia. A model of gene prediction trained on one(More)
Digital Signal Processing techniques constitute the basic scientific approach used in most of the current advances in medicine. In particular, the development of algorithms in order to extract, predict and model raw biomedical data series has revolutionized many routine, but data-intensive, areas of current medical practice. In this contribution, we present(More)
In this work, a well-tested evolutionary method for system modeling and time series prediction is presented. The method combines the effectiveness of adaptive multi model partitioning filters and GAs' robustness. Specifically, the a posteriori probability that a specific model, of a bank of the conditional models, is the true model can be used as fitness(More)
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