Geodata Scale Restriction using Genetic Algorithm

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F14%3A33148621" target="_blank" >RIV/61989592:15310/14:33148621 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_20" target="_blank" >http://dx.doi.org/10.1007/978-3-319-01781-5_20</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_20" target="_blank" >10.1007/978-3-319-01781-5_20</a>

Result language
angličtina
Original language name
Geodata Scale Restriction using Genetic Algorithm
Original language description
With recent advances in computer sciences (including geosciences) it is possible to combine various methods for geodata processing. There are many methods established for geodata scale restriction, but none of these take into account the concept of information entropy. Our research focused on using genetic algorithm that calculates information entropy in order to set an optimal number of intervals from original non-restricted geodata. We used fitness function by minimizing information entropy loss and we compared the results with commonly used classification method in geosciences. We propose an experimental method that provides promising approach for geodata scale restriction and consequent proper visualization, which is very important for geographicalphenomena interpretation
Czech name
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Czech description
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Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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