Abstract
In many areas of science and engineering it is of great interest to compute different statistics under the interval uncertainty. Unfortunately, this task often turns out to be very complex. For example, finding the bounds of the interval that includes all possible values produced by the calculation of quantities like variance or covariance for interval valued dataset is a NP-hard task. In this paper a genetic algorithm is proposed to tackle with this problem. An application of the algorithm is presented and compared with the result of an exhaustive search using the same data, which has been performed on a grid computing infrastructure.
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Acknowledgments
Work of the first author paper was supported by grants GAČR 201/09/0755 and MSM 0021620839. Work of the second author was supported by the project S.Co.P.E., Programma Operativo Nazionale 2000/2006, Ricerca Scientifica, Sviluppo Tecnologico, Alta Formazione.
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Antoch, J., Miele, R. (2011). Use of Genetic Algorithms When Computing Variance of Interval Data. In: Fichet, B., Piccolo, D., Verde, R., Vichi, M. (eds) Classification and Multivariate Analysis for Complex Data Structures. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13312-1_39
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DOI: https://doi.org/10.1007/978-3-642-13312-1_39
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