<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0188-6266</journal-id>
<journal-title><![CDATA[Acta universitaria]]></journal-title>
<abbrev-journal-title><![CDATA[Acta univ]]></abbrev-journal-title>
<issn>0188-6266</issn>
<publisher>
<publisher-name><![CDATA[Universidad de Guanajuato, Dirección de Investigación y Posgrado]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0188-62662022000100154</article-id>
<article-id pub-id-type="doi">10.15174/au.2022.3433</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Evaluación de la incertidumbre asociada a las proyecciones de precipitación considerando el cambio climático en la cuenca del río Turbio de Guanajuato]]></article-title>
<article-title xml:lang="en"><![CDATA[Evaluation of the uncertainty associated with precipitation projections considering climate change in the Turbio river basin of Guanajuato]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Martínez Bárcenas]]></surname>
<given-names><![CDATA[Adrián]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Herrera Fernández]]></surname>
<given-names><![CDATA[Manuel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Orozco Medina]]></surname>
<given-names><![CDATA[Ismael]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Guanajuato  ]]></institution>
<addr-line><![CDATA[Guanajuato ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,University of Cambridge Institute for Manufacturing Department of Engineering]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>United Kingdom</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad de Guanajuato  ]]></institution>
<addr-line><![CDATA[Guanajuato ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2022</year>
</pub-date>
<volume>32</volume>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0188-62662022000100154&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0188-62662022000100154&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0188-62662022000100154&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El cambio climático es el gran desafío del siglo XXI, cada año se incrementa la frecuencia y la magnitud de los fenómenos meteorológicos. Por lo tanto, resulta de gran importancia pronosticar las variables asociadas a este fenómeno, como la precipitación. Sin embargo, determinar e incorporar la incertidumbre asociada a las proyecciones de variables meteorológicas es un problema que requiere de mayor investigación. Es por ello que este artículo se enfoca a evaluar la incertidumbre a través del método de Monte Carlo, incluyendo las proyecciones de precipitaciones de los modelos de circulación general y el downscaling con redes neuronales artificiales (RNA). Los resultados obtenidos muestran que el downscaling con las RNA reduce significativamente la incertidumbre a las proyecciones de los modelos de circulación general. Se observa también una tendencia a subestimar las precipitaciones en la mayoría de las estaciones y un sesgo en los outputs respecto a la serie histórica.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Climate change is the great challenge of the 21st century, each year the frequency and magnitude of weather increases. Therefore, it is of importance to forecast the variables associated to this phenomenon, such as precipitation. However, determining and incorporating the uncertainty associated with projections of meteorological variables is a problem that requires further investigation. For this reason, this research focuses on evaluating the uncertainty through Monte Carlo, including the precipitation projections of the general circulation models and downscaling with artificial neural networks. The results obtained show that downscaling with artificial neural networks significantly reduces the uncertainty to the projections of the general circulation models. Furthermore, there is a tendency to underestimate rainfall in most of the stations along with bias in the outputs related to the historical series.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Incertidumbre]]></kwd>
<kwd lng="es"><![CDATA[cambio climático]]></kwd>
<kwd lng="es"><![CDATA[Monte Carlo]]></kwd>
<kwd lng="es"><![CDATA[downscaling]]></kwd>
<kwd lng="es"><![CDATA[redes neuronales artificiales]]></kwd>
<kwd lng="en"><![CDATA[Uncertainty]]></kwd>
<kwd lng="en"><![CDATA[climate change]]></kwd>
<kwd lng="en"><![CDATA[Monte Carlo]]></kwd>
<kwd lng="en"><![CDATA[downscaling]]></kwd>
<kwd lng="en"><![CDATA[artificial neural network]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Arnell]]></surname>
<given-names><![CDATA[N.W.]]></given-names>
</name>
<name>
<surname><![CDATA[Lloyd-Hughes]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios]]></article-title>
<source><![CDATA[Climatic Change]]></source>
<year>2014</year>
<volume>122</volume>
<page-range>127-40</page-range></nlm-citation>
</ref>
<ref id="B2">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Bates]]></surname>
<given-names><![CDATA[B. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Kundzewicz]]></surname>
<given-names><![CDATA[Z. W.]]></given-names>
</name>
<name>
<surname><![CDATA[Wu]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Palutikof]]></surname>
<given-names><![CDATA[J. P.]]></given-names>
</name>
</person-group>
<source><![CDATA[Climate change and water. Technical paper of the Intergovernmental Panel on Climate Change, IPCC]]></source>
<year>2008</year>
</nlm-citation>
</ref>
<ref id="B3">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Blasone]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Madsen]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Rosbjerg]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Uncertainty assessment of integrated distributed hydrological models using GLUE with Markov chain Monte Carlo sampling]]></article-title>
<source><![CDATA[Journal of Hydrology]]></source>
<year>2008</year>
<volume>353</volume>
<numero>1-2</numero>
<issue>1-2</issue>
<page-range>18-32</page-range></nlm-citation>
</ref>
<ref id="B4">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Bouwer]]></surname>
<given-names><![CDATA[L. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Aerts]]></surname>
<given-names><![CDATA[J. C. J. H.]]></given-names>
</name>
<name>
<surname><![CDATA[van de Coterlet]]></surname>
<given-names><![CDATA[G. M.]]></given-names>
</name>
<name>
<surname><![CDATA[van de Giesen]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Gieske]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Mannaerts]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Evaluating downscaling methods for preparing global circulation model (GCM) data for hydrological impact modelling]]></article-title>
<person-group person-group-type="editor">
<name>
<surname><![CDATA[Aerts]]></surname>
<given-names><![CDATA[J.C.J.H.]]></given-names>
</name>
<name>
<surname><![CDATA[Droogers]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
</person-group>
<source><![CDATA[Climate Change in Contrasting River Basins adaptation strategies for water, food, and environment]]></source>
<year>2004</year>
<edition>1</edition>
<page-range>25-48</page-range><publisher-name><![CDATA[CABI Publishing]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B5">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Delgado]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Ledesma]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Rostro]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Análisis de electroencefalograma usando redes neuronales artificiales]]></article-title>
<source><![CDATA[Acta Universitaria]]></source>
<year>2019</year>
<volume>28</volume>
</nlm-citation>
</ref>
<ref id="B6">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gaillard]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Liamzon]]></surname>
<given-names><![CDATA[C. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Maceda]]></surname>
<given-names><![CDATA[E. A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Act of Nature or Act of Man? Tracking the root causes of increasing disasters in the Philippines]]></article-title>
<source><![CDATA[Philippine Geographical Journal]]></source>
<year>2005</year>
<volume>49</volume>
<numero>1-4</numero>
<issue>1-4</issue>
<page-range>46-65</page-range></nlm-citation>
</ref>
<ref id="B7">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Guha-Sapir]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Hoyois]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Wallemacq]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Below]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<source><![CDATA[Annual Disaster Statistical Review 2016. The numbers and trends]]></source>
<year>2016</year>
<publisher-name><![CDATA[UCL]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B8">
<nlm-citation citation-type="">
<collab>Earth System Grid Generation-Lawrence Livermore National Laboratory</collab>
<source><![CDATA[Página principal del Earth System Grid Federation (ESGF)]]></source>
<year>2020</year>
</nlm-citation>
</ref>
<ref id="B9">
<nlm-citation citation-type="book">
<collab>Intergovernmental Panel of Climate Change</collab>
<source><![CDATA[Cambio climático 2014: Impactos, adaptación y vulnerabilidad - Resumen para responsables de políticas]]></source>
<year>2014</year>
<publisher-name><![CDATA[Organización Meteorológica Mundial]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B10">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Janssen]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Monte-Carlo based uncertainty analysis: sampling efficiency and sampling convergence]]></article-title>
<source><![CDATA[Reliability Engineering &amp; System Safety]]></source>
<year>2013</year>
<volume>109</volume>
<page-range>123-32</page-range></nlm-citation>
</ref>
<ref id="B11">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lee]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Kim]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Lee]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Kim]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Kim]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Medium-term rainfall forecasts using artificial neural networks with Monte-Carlo cross-validation and aggregation for the Han River Basin, Korea]]></article-title>
<source><![CDATA[Water]]></source>
<year>2020</year>
<volume>12</volume>
<numero>6</numero>
<issue>6</issue>
</nlm-citation>
</ref>
<ref id="B12">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mae]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Kumagai]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Kanamori]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Uncertainty propagation for dropout-based Bayesian neural networks]]></article-title>
<source><![CDATA[Neural Networks]]></source>
<year>2021</year>
<volume>144</volume>
<page-range>394-406</page-range></nlm-citation>
</ref>
<ref id="B13">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Matott]]></surname>
<given-names><![CDATA[L. S.]]></given-names>
</name>
<name>
<surname><![CDATA[Babendreier]]></surname>
<given-names><![CDATA[J. E.]]></given-names>
</name>
<name>
<surname><![CDATA[Purucker]]></surname>
<given-names><![CDATA[S. T.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Evaluating uncertainty in integrated environmental models: a review of concepts and tools]]></article-title>
<source><![CDATA[Water Resources Research]]></source>
<year>2009</year>
<volume>45</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>1-14</page-range></nlm-citation>
</ref>
<ref id="B14">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[McSweeney]]></surname>
<given-names><![CDATA[C. F.]]></given-names>
</name>
<name>
<surname><![CDATA[Jones]]></surname>
<given-names><![CDATA[R. G.]]></given-names>
</name>
<name>
<surname><![CDATA[Lee]]></surname>
<given-names><![CDATA[R. W.]]></given-names>
</name>
<name>
<surname><![CDATA[Rowell]]></surname>
<given-names><![CDATA[D. P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Selecting CMIP5 GCMs for downscaling over multiple regions]]></article-title>
<source><![CDATA[Climate Dynamics]]></source>
<year>2015</year>
<volume>44</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>3237-60</page-range></nlm-citation>
</ref>
<ref id="B15">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Muñoz]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
<name>
<surname><![CDATA[Tume]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Ortíz]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Uncertainty in rainfall input data in a conceptual water balance model: effects on outputs and implications for predictability]]></article-title>
<source><![CDATA[Earth Sciences Research Journal]]></source>
<year>2014</year>
<volume>18</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>69-75</page-range></nlm-citation>
</ref>
<ref id="B16">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Orozco]]></surname>
<given-names><![CDATA[I.]]></given-names>
</name>
<name>
<surname><![CDATA[Martínez]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Ortega]]></surname>
<given-names><![CDATA[V.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Assessment of the water, environmental, economic and social vulnerability of a watershed to the potential effects of climate change and land use change]]></article-title>
<source><![CDATA[Water]]></source>
<year>2020</year>
<volume>12</volume>
<numero>6</numero>
<issue>6</issue>
</nlm-citation>
</ref>
<ref id="B17">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Oyebode]]></surname>
<given-names><![CDATA[O.]]></given-names>
</name>
<name>
<surname><![CDATA[Stretch]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Neural network modeling of hydrological systems: a review of implementation techniques]]></article-title>
<source><![CDATA[Natural Resource Modeling]]></source>
<year>2019</year>
<volume>32</volume>
</nlm-citation>
</ref>
<ref id="B18">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Padhiary]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Patra]]></surname>
<given-names><![CDATA[K. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Dash]]></surname>
<given-names><![CDATA[S. S.]]></given-names>
</name>
<name>
<surname><![CDATA[Kumar]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Climate change impact assessment on hydrological fluxes based on ensemble GCM outputs: a case study in eastern Indian River Basin]]></article-title>
<source><![CDATA[Journal of Water and Climate Change]]></source>
<year>2019</year>
<volume>11</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>1676-94</page-range></nlm-citation>
</ref>
<ref id="B19">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Parodi]]></surname>
<given-names><![CDATA[J. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Rodríguez]]></surname>
<given-names><![CDATA[J. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Rodríguez]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[La nueva generación de modelos climáticos. El proyecto europeo EC-Earth]]></article-title>
<source><![CDATA[Acta de las Jornadas Científicas de la Asociación Meteorológica Española]]></source>
<year>2020</year>
</nlm-citation>
</ref>
<ref id="B20">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rajabi]]></surname>
<given-names><![CDATA[M. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Ataie-Ashtiani]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Janssen]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Efficiency enhancement of optimized Latin hypercube sampling strategies: application to Monte Carlo uncertainty analysis and meta-modeling]]></article-title>
<source><![CDATA[Advances in Water Resources]]></source>
<year>2015</year>
<volume>76</volume>
<page-range>127-39</page-range></nlm-citation>
</ref>
<ref id="B21">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Refsgaard]]></surname>
<given-names><![CDATA[J. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Van der Sluijs]]></surname>
<given-names><![CDATA[J. P.]]></given-names>
</name>
<name>
<surname><![CDATA[Højberg]]></surname>
<given-names><![CDATA[A. L.]]></given-names>
</name>
<name>
<surname><![CDATA[Vanrolleghem]]></surname>
<given-names><![CDATA[P. A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Uncertainty in the environmental modelling process - A framework and guidance]]></article-title>
<source><![CDATA[Environmental Modelling &amp; Software]]></source>
<year>2007</year>
<volume>22</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>1543-56</page-range></nlm-citation>
</ref>
<ref id="B22">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Taylor]]></surname>
<given-names><![CDATA[K. E.]]></given-names>
</name>
<name>
<surname><![CDATA[Stouffer]]></surname>
<given-names><![CDATA[R. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Meehl]]></surname>
<given-names><![CDATA[G. A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[An overview of CMIP5 and the experiment design]]></article-title>
<source><![CDATA[Bulletin of the American Meteorological Society]]></source>
<year>2012</year>
<volume>93</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>485-98</page-range></nlm-citation>
</ref>
<ref id="B23">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Gao]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Yu]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Bayesian forecasting and uncertainty quantifying of stream flows using Metropolis-Hastings Markov Chain Monte Carlo algorithm]]></article-title>
<source><![CDATA[Journal of Hydrology]]></source>
<year>2017</year>
<volume>549</volume>
<page-range>476-83</page-range></nlm-citation>
</ref>
<ref id="B24">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wunderli]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Uncertainty evaluation in general including simple artificial applications and Monte Carlo uncertainty evaluation]]></article-title>
<source><![CDATA[Journal of Physics: Conference Series]]></source>
<year>2019</year>
<volume>1420</volume>
</nlm-citation>
</ref>
<ref id="B25">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zanotti]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Rotiroti]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Sterlacchini]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Cappellini]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Fumagalli]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Stefania]]></surname>
<given-names><![CDATA[G. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Nannucci]]></surname>
<given-names><![CDATA[M. S.]]></given-names>
</name>
<name>
<surname><![CDATA[Leoni]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Bonomi]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Choosing between linear and nonlinear models and avoiding overfitting for short and long term groundwater level forecasting in a linear system]]></article-title>
<source><![CDATA[Journal of Hydrology]]></source>
<year>2019</year>
<volume>578</volume>
</nlm-citation>
</ref>
<ref id="B26">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhou]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Aghili]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Ghaleini]]></surname>
<given-names><![CDATA[E. N.]]></given-names>
</name>
<name>
<surname><![CDATA[Bui]]></surname>
<given-names><![CDATA[D. T.]]></given-names>
</name>
<name>
<surname><![CDATA[Tahir]]></surname>
<given-names><![CDATA[M. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Koopialipoor]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Monte Carlo simulation approach for effective assessment of flyrock based on intelligent system of neural network]]></article-title>
<source><![CDATA[Engineering with Computers]]></source>
<year>2020</year>
<volume>36</volume>
<page-range>713-23</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
