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Ising model for interpolation of spatial data on regular grids

Žukovič, Milan, Christopoulos Dionysios

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URIhttp://purl.tuc.gr/dl/dias/8474B456-F110-467C-A572-3F901DEA5A5F-
Αναγνωριστικόhttps://doi.org/10.3390/e23101270-
Αναγνωριστικόhttps://www.mdpi.com/1099-4300/23/10/1270/htm-
Γλώσσαen-
Μέγεθος18 pagesen
ΤίτλοςIsing model for interpolation of spatial data on regular gridsen
ΔημιουργόςŽukovič, Milanen
ΔημιουργόςChristopoulos Dionysiosen
ΔημιουργόςΧριστοπουλος Διονυσιοςel
ΕκδότηςMDPIen
ΠερίληψηWe apply the Ising model with nearest-neighbor correlations (INNC) in the problem of interpolation of spatially correlated data on regular grids. The correlations are captured by short-range interactions between “Ising spins”. The INNC algorithm can be used with label data (classification) as well as discrete and continuous real-valued data (regression). In the regression problem, INNC approximates continuous variables by means of a user-specified number of classes. INNC predicts the class identity at unmeasured points by using the Monte Carlo simulation conditioned on the observed data (partial sample). The algorithm locally respects the sample values and globally aims to minimize the deviation between an energy measure of the partial sample and that of the entire grid. INNC is non-parametric and, thus, is suitable for non-Gaussian data. The method is found to be very competitive with respect to interpolation accuracy and computational efficiency compared to some standard methods. Thus, this method provides a useful tool for filling gaps in gridded data such as satellite images.en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2022-09-29-
Ημερομηνία Δημοσίευσης2021-
Θεματική ΚατηγορίαIsing modelen
Θεματική ΚατηγορίαSpatial classificationen
Θεματική ΚατηγορίαInterpolationen
Θεματική ΚατηγορίαNon-Gaussian dataen
Θεματική ΚατηγορίαEarth observationen
Θεματική ΚατηγορίαFast algorithmen
Βιβλιογραφική ΑναφοράM. Žukovič and D. T. Hristopulos, “Ising model for interpolation of spatial data on regular grids,” Entropy, vol. 23, no. 10, Sep. 2021, doi: 10.3390/e23101270.en

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