From interval computations to constraint-related set computations: Towards faster estimation of statistics and ODEs under interval, p-Box, and fuzzy uncertainty

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Abstract

In interval computations, at each intermediate stage of the computation, we have intervals of possible values of the corresponding quantities. In our previous papers, we proposed an extension of this technique to set computations, where on each stage, in addition to intervals of possible values of the quantities, we also keep sets of possible values of pairs (triples, etc.). In this paper, we show that in several practical problems, such as estimating statistics (variance, correlation, etc.) and solutions to ordinary differential equations (ODEs) with given accuracy, this new formalism enables us to find estimates in feasible (polynomial) time. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Ceberio, M., Kreinovich, V., Pownuk, A., & Bede, B. (2007). From interval computations to constraint-related set computations: Towards faster estimation of statistics and ODEs under interval, p-Box, and fuzzy uncertainty. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4529 LNAI, pp. 33–42). Springer Verlag. https://doi.org/10.1007/978-3-540-72950-1_4

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