<?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>1815-5928</journal-id>
<journal-title><![CDATA[Ingeniería Electrónica, Automática y Comunicaciones]]></journal-title>
<abbrev-journal-title><![CDATA[EAC]]></abbrev-journal-title>
<issn>1815-5928</issn>
<publisher>
<publisher-name><![CDATA[Universidad Tecnológica de La Habana José Antonio Echeverría, Cujae]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1815-59282023000300041</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Sistema para la toma de decisiones en el riego de cultivos protegidos basado en aprendizaje de máquina]]></article-title>
<article-title xml:lang="en"><![CDATA[Decision-making system for irrigation of protected crops based on machine learning]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Villavicencio_Quintero]]></surname>
<given-names><![CDATA[Dennis]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cabrera_Hernández]]></surname>
<given-names><![CDATA[Emilio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Godo_Alonso]]></surname>
<given-names><![CDATA[Alain]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Santana Ching]]></surname>
<given-names><![CDATA[Ivan]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Central Marta Abreu de Las Villas  ]]></institution>
<addr-line><![CDATA[Villa Clara ]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,SORBA.ai  ]]></institution>
<addr-line><![CDATA[Jacksonville FL]]></addr-line>
<country>USA</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2023</year>
</pub-date>
<volume>44</volume>
<numero>3</numero>
<fpage>41</fpage>
<lpage>49</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S1815-59282023000300041&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S1815-59282023000300041&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S1815-59282023000300041&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La escasez de agua constituye una preocupación de la industria agropecuaria, y es que esta emplea en la irrigación cuatro quintas partes del total de agua fresca consumida y dos tercios del total empleado para consumo humano. Por tal razón resulta esencial el desarrollo de sistemas que optimicen el empleo de agua en el riego. En las casas de cultivo protegido de la UEB &#8220;Valle del Yabú&#8221; del municipio Santa Clara el riego se realiza mediante un sistema basado en goteo que requiere la presencia de un operario para la toma de decisiones, el cual no tiene información sobre algunas de las variables hidrometeorológicas que rigen al cultivo. Este artículo se centró en diseñar un sistema de apoyo a la toma de decisiones en el riego basado en aprendizaje de máquina. Como parámetro de importancia del sistema se calcula el coeficiente de evapotranspiración del cultivo utilizando para ello la fórmula de Turc. Se realiza un acondicionamiento de los datos ambientales recopilados y con ellos se entrenan modelos de regresión lineal, bosques aleatorios regresivos y bosques aleatorios de gradiente mejorado para determinar valores de evapotranspiración futuros empleando la plataforma Apache Spark. El modelo que obtuvo los mejores resultados fue el bosque aleatorio regresivo con un coeficiente de determinación (r2) de 0,79 y con él se calcula el volumen de agua perdido por el cultivo. Finalmente, el sistema fue capaz de proveer las estimaciones de ambas variables las que favorecen la toma de decisiones por parte de los especialistas.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The water scarcity is a concern of the agricultural industry as it uses four fifths of the of the total fresh water consumed for irrigation and two thirds of the total used for human consumption. For this reason, the development of systems that optimize the use of water in irrigation is essential. In the greenhouses of the UEB "Valle del Yabú" of the Santa Clara municipality, irrigation is carried out using a drip-based system that requires the presence of an operator for decision-making who does not have information about some of the hydrometeorological variables that govern the crop. This paper focused on to design a support system for decision-making in irrigation based on machine learning. As an important parameter of the system, the evapotranspiration coefficient of the crop is calculated using the Turc formula. The collected environmental data is conditioned and linear regression, regressive random forests, and gradient-boosted trees regression models are trained with them to determine future evapotranspiration values using the Apache Spark framework. The model that obtained the best results was the regressive random forest with a coefficient of determination (r2) of 0,79 and with it the volume of water lost by the crop is calculated. Finally, the system was able to provide the estimates of both variables, which favour decision-making by specialists.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[cultivo protegido]]></kwd>
<kwd lng="es"><![CDATA[inteligencia artificial]]></kwd>
<kwd lng="es"><![CDATA[aprendizaje de máquina]]></kwd>
<kwd lng="es"><![CDATA[evapotranspiración]]></kwd>
<kwd lng="es"><![CDATA[bosques aleatorios regresivos]]></kwd>
<kwd lng="en"><![CDATA[greenhouse cultivation]]></kwd>
<kwd lng="en"><![CDATA[artificial intelligence]]></kwd>
<kwd lng="en"><![CDATA[machine learning]]></kwd>
<kwd lng="en"><![CDATA[evapotranspiration]]></kwd>
<kwd lng="en"><![CDATA[random regressive forests]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<label>1.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Pérez Vázquez]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Leyva Trinidad]]></surname>
<given-names><![CDATA[DA]]></given-names>
</name>
<name>
<surname><![CDATA[Gómez Merino]]></surname>
<given-names><![CDATA[FC.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Desafíos y propuestas para lograr la seguridad alimentaria hacia el año 2050]]></article-title>
<source><![CDATA[Revista mexicana de ciencias agrícolas]]></source>
<year>2018</year>
<volume>9</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>175-89</page-range></nlm-citation>
</ref>
<ref id="B2">
<label>2.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Zhao]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Wen]]></surname>
<given-names><![CDATA[Q.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Farmers&#8217; adoption intentions of water-saving agriculture under the risks of frequent irrigation-induced landslides]]></article-title>
<source><![CDATA[Climate Risk Management]]></source>
<year>2023</year>
<volume>39</volume>
</nlm-citation>
</ref>
<ref id="B3">
<label>3.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Abd-Elaty]]></surname>
<given-names><![CDATA[I]]></given-names>
</name>
<name>
<surname><![CDATA[Fathy]]></surname>
<given-names><![CDATA[I]]></given-names>
</name>
<name>
<surname><![CDATA[Kuriqi]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[John]]></surname>
<given-names><![CDATA[AP]]></given-names>
</name>
<name>
<surname><![CDATA[Straface]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Ramadan]]></surname>
<given-names><![CDATA[EM.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Impact of Modern Irrigation Methods on Groundwater Storage and Land Subsidence in High-water Stress Regions]]></article-title>
<source><![CDATA[Water Resources Management]]></source>
<year>2023</year>
<volume>37</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>1827-40</page-range></nlm-citation>
</ref>
<ref id="B4">
<label>4.</label><nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gamal]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Soltan]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Said]]></surname>
<given-names><![CDATA[LA]]></given-names>
</name>
<name>
<surname><![CDATA[Madian]]></surname>
<given-names><![CDATA[AH]]></given-names>
</name>
<name>
<surname><![CDATA[Radwan]]></surname>
<given-names><![CDATA[AG.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Smart Irrigation Systems]]></article-title>
<source><![CDATA[Overview. IEEE Access]]></source>
<year>2023</year>
<page-range>1</page-range></nlm-citation>
</ref>
<ref id="B5">
<label>5.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Vallejo-Gómez]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Osorio]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Hincapié]]></surname>
<given-names><![CDATA[CA.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Smart Irrigation Systems in Agriculture: A Systematic Review]]></article-title>
<source><![CDATA[Agronomy]]></source>
<year>2023</year>
<volume>13</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>342</page-range></nlm-citation>
</ref>
<ref id="B6">
<label>6.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cardenas Rivero]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[De la Paz]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Portal]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Duran-Faundez]]></surname>
<given-names><![CDATA[I.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Potentialities of data processing in internet of things applications]]></article-title>
<source><![CDATA[International Journal of Embedded Systems]]></source>
<year>2021</year>
<volume>14</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>486-96</page-range></nlm-citation>
</ref>
<ref id="B7">
<label>7.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Osinga]]></surname>
<given-names><![CDATA[SA]]></given-names>
</name>
<name>
<surname><![CDATA[Paudel]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Mouzakitis]]></surname>
<given-names><![CDATA[SA]]></given-names>
</name>
<name>
<surname><![CDATA[Athanasiadis]]></surname>
<given-names><![CDATA[IN]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Big data in agriculture: Between opportunity and solution]]></article-title>
<source><![CDATA[Agricultural Systems]]></source>
<year>2022</year>
<volume>195</volume>
</nlm-citation>
</ref>
<ref id="B8">
<label>8.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Madruga-Peláez]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Estevez-Pérez]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Sosa]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Garcia Algora]]></surname>
<given-names><![CDATA[CM]]></given-names>
</name>
<name>
<surname><![CDATA[Santana]]></surname>
<given-names><![CDATA[I.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Red de Sensores Inalámbricos para la Adquisición de Datos en Casas de Cultivo]]></article-title>
<source><![CDATA[Ingeniería]]></source>
<year>2019</year>
<volume>24</volume>
<page-range>224-34</page-range></nlm-citation>
</ref>
<ref id="B9">
<label>9.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Tantalaki]]></surname>
<given-names><![CDATA[N]]></given-names>
</name>
<name>
<surname><![CDATA[Souravlas]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Roumeliotis]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Data-Driven Decision Making in Precision Agriculture: The Rise of Big Data inAgricultural Systems]]></article-title>
<source><![CDATA[Journal of Agricultural &amp; Food Information]]></source>
<year>2019</year>
<volume>20</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>344-80</page-range></nlm-citation>
</ref>
<ref id="B10">
<label>10.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cravero]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Pardo]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Sepúlveda]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Muñoz]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Challenges to Use Machine Learning in Agricultural Big Data: A Systematic Literature Review]]></article-title>
<source><![CDATA[Agronomy]]></source>
<year>2022</year>
<volume>12</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>748</page-range></nlm-citation>
</ref>
<ref id="B11">
<label>11.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Tang]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Aridas]]></surname>
<given-names><![CDATA[NK]]></given-names>
</name>
<name>
<surname><![CDATA[Talip]]></surname>
<given-names><![CDATA[MSA.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Design of a data processing method for the farmland environmental monitoring based on improved Spark components]]></article-title>
<source><![CDATA[Front Big Data]]></source>
<year>2023</year>
<volume>6</volume>
</nlm-citation>
</ref>
<ref id="B12">
<label>12.</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Madhuri]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Indiramma]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Big Data Analytics-Based Agro Advisory System for Crop Recommendation Using Spark Platform]]></article-title>
<source><![CDATA[Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics]]></source>
<year>2023</year>
<page-range>227-47</page-range><publisher-loc><![CDATA[Hershey, PA, USA ]]></publisher-loc>
<publisher-name><![CDATA[IGI Global]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B13">
<label>13.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[James]]></surname>
<given-names><![CDATA[N]]></given-names>
</name>
<name>
<surname><![CDATA[Ong]]></surname>
<given-names><![CDATA[L-Y]]></given-names>
</name>
<name>
<surname><![CDATA[Leow]]></surname>
<given-names><![CDATA[M-C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Exploring Distributed Deep Learning Inference Using Raspberry Pi Spark Cluster]]></article-title>
<source><![CDATA[Future Internet]]></source>
<year>2022</year>
<volume>14</volume>
<numero>8</numero>
<issue>8</issue>
<page-range>220</page-range></nlm-citation>
</ref>
<ref id="B14">
<label>14.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Romero]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Rázuri]]></surname>
<given-names><![CDATA[LR]]></given-names>
</name>
<name>
<surname><![CDATA[Suniaga]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Montilla]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Estimación de las necesidades hídricas del cultivo de pepino (Cucumis Sativus L.) Durante las diferentes etapas fenológicas, mediante la tina de evaporación]]></article-title>
<source><![CDATA[Agricultura andina]]></source>
<year>2009</year>
<volume>16</volume>
<page-range>56-69</page-range></nlm-citation>
</ref>
<ref id="B15">
<label>15.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gloria]]></surname>
<given-names><![CDATA[I E]]></given-names>
</name>
<name>
<surname><![CDATA[Nkpouto]]></surname>
<given-names><![CDATA[L T]]></given-names>
</name>
<name>
<surname><![CDATA[Felix]]></surname>
<given-names><![CDATA[U A]]></given-names>
</name>
<name>
<surname><![CDATA[Sunday]]></surname>
<given-names><![CDATA[E O.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[An overview of uncertainties in evapotranspiration estimation techniques]]></article-title>
<source><![CDATA[Journal of Agrometeorology]]></source>
<year>2023</year>
<volume>25</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>173-82</page-range></nlm-citation>
</ref>
<ref id="B16">
<label>16.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Niranjan]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Nandagiri]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Performance evaluation of simpler reference crop evapotranspiration estimation equations with and without local calibration]]></article-title>
<source><![CDATA[Journal of Applied Water Engineering and Research]]></source>
<year>2023</year>
<page-range>1-18</page-range></nlm-citation>
</ref>
<ref id="B17">
<label>17.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Goyal]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Kumar]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Sharda]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A review of the Artificial Intelligence (AI) based techniques for estimating reference evapotranspiration: Current trends and future perspectives]]></article-title>
<source><![CDATA[Computers and Electronics in Agriculture]]></source>
<year>2023</year>
<volume>209</volume>
</nlm-citation>
</ref>
<ref id="B18">
<label>18.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Makwana]]></surname>
<given-names><![CDATA[JJ]]></given-names>
</name>
<name>
<surname><![CDATA[Tiwari]]></surname>
<given-names><![CDATA[MK]]></given-names>
</name>
<name>
<surname><![CDATA[Deora]]></surname>
<given-names><![CDATA[BS.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Development and comparison of artificial intelligence models for estimating daily reference evapotranspiration from limited input variables]]></article-title>
<source><![CDATA[Smart Agricultural Technology]]></source>
<year>2023</year>
<volume>3</volume>
</nlm-citation>
</ref>
<ref id="B19">
<label>19.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Yong]]></surname>
<given-names><![CDATA[SLS]]></given-names>
</name>
<name>
<surname><![CDATA[Ng]]></surname>
<given-names><![CDATA[JL]]></given-names>
</name>
<name>
<surname><![CDATA[Huang]]></surname>
<given-names><![CDATA[YF]]></given-names>
</name>
<name>
<surname><![CDATA[Ang]]></surname>
<given-names><![CDATA[CK.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Estimation of Reference Crop Evapotranspiration with Three Different Machine Learning Models and Limited Meteorological Variables]]></article-title>
<source><![CDATA[Agronomy]]></source>
<year>2023</year>
<volume>13</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>1048</page-range></nlm-citation>
</ref>
<ref id="B20">
<label>20.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Güzel]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
<name>
<surname><![CDATA[Üne&#351;]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Erginer]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Kaya]]></surname>
<given-names><![CDATA[YZ]]></given-names>
</name>
<name>
<surname><![CDATA[Ta&#351;ar]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
<name>
<surname><![CDATA[Erginer]]></surname>
<given-names><![CDATA[&#304;]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A comparative study on daily evapotranspiration estimation by using various artificial intelligence techniques and traditional regression calculations]]></article-title>
<source><![CDATA[Mathematical Biosciences and Engineering]]></source>
<year>2023</year>
<volume>20</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>11328-52</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
