Abstract
One of the methodologies more used to accomplish prospective analysis is the scenario method. The first stage of this method is the so called structural analysis and aims to determine the most important variables of a system. Despite being widely used, structural analysis still presents some shortcomings, mainly due to the vagueness of the information used in this process. In this sense, the application of Soft Computing to structural analysis can contribute to reduce the impact of these problems by providing more interpretable and robust models. With this in mind, we present a methodology for structural analysis based on computing with words techniques to properly address vagueness and increase the interpretability. The method has been applied to a real problem with encouraging results.
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Villacorta, P.J., Masegosa, A.D., Castellanos, D., Lamata, M.T. (2012). A Linguistic Approach to Structural Analysis in Prospective Studies. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances on Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31709-5_16
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DOI: https://doi.org/10.1007/978-3-642-31709-5_16
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