Abstract
This paper presents an algorithm, different from the classical time series, specialised in extracting knowledge from time series. The algorithm, based on Genetic Programming, enables the dynamic introduction of non-terminal operators shaped as mathematical expressions (operator-expression) that works as an unique node for the purpose of genetic operations (crossover and mutation). A new characteristic of this algorithm is the possibility of expansion the individuals, which, besides inducing a better global fitness, enables breaking up the expressions (operator-expression) into basic operators in order to achieve expression recombination. The performance of the implemented algorithm was showed by means of its application to the creep of structural concrete, a specific case of Construction Engineering where a best adjustment to the current regulative codes was subsequently achieved.
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Pérez, J.L., Abella, F.M., Catoira, A., Berrocal, J. (2009). Special Time Series Prediction: Creep of Concrete. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds) Bio-Inspired Systems: Computational and Ambient Intelligence. IWANN 2009. Lecture Notes in Computer Science, vol 5517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02478-8_148
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DOI: https://doi.org/10.1007/978-3-642-02478-8_148
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