Deterministic Prediction Theory

Nicholas J. Daras ()
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Nicholas J. Daras: Hellenic Military Academy, Department of Mathematics and Engineering Sciences

A chapter in Approximation Theory and Analytic Inequalities, 2021, pp 87-137 from Springer

Abstract: Abstract We give a general method for predicting spatio-temporal regions with “strange” systemic occurrences. To do so, we consider systemic indices and their measurements into the under consideration fixed spatio-temporal region. Given a set of preselected future points, the magnitude of the (Euclidean or not) distance between the surface of these systemic indices and a parametrized surface that interpolates or passes very close to the points of systemic measurements and given preselected vector values may be viewed as a measure for assessing the appearance of peculiar systemic incidents over the region under consideration; so, depending on these preselected points, we provide a general algorithmic framework for predicting spatio-temporal regions into which crucial systemic events are expected.

Keywords: Systemic analysis; Universality of systemic indices; Parametrized surface; Section of systemic measurement; Prediction theory; Interpolation; Linear splines; Smoothing; Curve fitting; Mathematical modelling (models of systems; model matching; etc.); Realization from input–output data; Data smoothing; Least squares and related methods; 60G25; 65D05; 65D07; 65D10; 93A10; 93A30; 93B 15; 93E14; 93E24 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-60622-0_7

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DOI: 10.1007/978-3-030-60622-0_7

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