<?xml version="1.0"?><!DOCTYPE rdf:RDF SYSTEM "http://dublincore.org/documents/2000/11/dcmes-xml/dcmes-xml-dtd.dtd"><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description about="https://trilogia.utem.cl/articulos/structured-grammatical-evolution-for-modeling-the-multi-band-light-curves-of-supernova/"><dc:title>Structured grammatical evolution for modeling the multi-band light curves of supernova</dc:title><dc:date>2023-04-24</dc:date><dc:date>2023-04-24</dc:date></rdf:Description><article><front><journal-meta><journal-title>Structured grammatical evolution for modeling the multi-band light curves of supernova</journal-title><issn>2452-5995</issn></journal-meta><article-meta><pub-date pub-type="pub"><day>24</day><month>04</month><year>2023</year></pub-date><volume>38</volume><numero>49</numero></article-meta></front><body><![CDATA[&lt;p&gt;&lt;strong&gt;ABSTRACT&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;Supernovas (SNs) have been one of the most studied events in astronomy. However, there are still no models capable of describing this phenomenon in a general and accurate way. These models generally seek to describe a single type of supernova, requires multiple parameter&rsquo;s values and often do not distinguish between the different light bands of the same curve. Structured grammatical evolution allows&lt;br /&gt;
the generation of a model with data and a given basal structure, which can be designed considering the nature of the problem for which we are looking for a model. In this case, with some mathematical assumptions we can generate a symbolic regression to obtain a model for different types of SNs and for each light band. We can also use this algorithm to fit the parametric model of the supernova and obtain the value of the variables needed to model it.&lt;/p&gt;
&lt;p&gt;RESUMEN&lt;/p&gt;
&lt;p&gt;Las supernovas (SN) han sido eventos muy estudiados por la astronom&iacute;a. Sin embargo, a&uacute;n no existen modelos capaces de describir este fen&oacute;meno de manera general y precisa. Estos modelos generalmente buscan describir un solo tipo de supernova, requieren m&uacute;ltiples valores de par&aacute;metros y, a menudo, no distinguen entre las diferentes bandas de luz de una misma curva. La evoluci&oacute;n gramatical estructurada permite generar un modelo con datos y una estructura base determinada que puede dise&ntilde;arse teniendo en cuenta la naturaleza del problema para el que buscamos un modelo. En este caso, con algunas suposiciones matem&aacute;ticas podemos generar una regresi&oacute;n simb&oacute;lica para obtener un modelo para diferentes tipos de SN y para cada banda de luz. Tambi&eacute;n podemos usar este algoritmo para ajustar el modelo param&eacute;trico de la supernova y obtener el valor de las variables necesarias para modelarlo.&lt;/p&gt;
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