<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="https://www.zbc.uz.zgora.pl/repozytorium/style/common/xsl/oai-style.xsl"?>
<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" 
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/
         http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd">
	<responseDate>2026-06-28T05:05:59Z</responseDate>
	<request identifier="oai:zbc.uz.zgora.pl:58996" metadataPrefix="oai_dc" verb="GetRecord">
	https://zbc.uz.zgora.pl/repozytorium/oai-pmh-repository.xml</request>
	<GetRecord>
	
  <record>
	<header>
		<identifier>oai:zbc.uz.zgora.pl:58996</identifier>
	    <datestamp>2025-07-14T12:34:36Z</datestamp>
		  <setSpec>DigitalLibraryZielonaGora</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:Faculties:FacultyComputerElectricalControl</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:ListJurnals:AMCS:AMCS12</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:Faculties</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:TypesWork</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:TypesWork:Articles</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:ListJurnals</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:ListJurnals:AMCS</setSpec> 	    </header>
		<metadata>
	<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title xml:lang="pl"><![CDATA[A rainfall forecasting method using machine learning models and its application to the Fukuoka city case]]></dc:title>
<dc:creator><![CDATA[Sumi, Monira S.]]></dc:creator>
<dc:creator><![CDATA[Zaman, Faisal M.]]></dc:creator>
<dc:creator><![CDATA[Hirose, Hideo]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[rainfall forecasting]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[machine learning]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[multi-model method]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[pre-processing]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[model ranking]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[In the present article, an attempt is made to derive optimal data-driven machine learning methods for forecasting an average daily and monthly rainfall of the Fukuoka city in Japan. This comparative study is conducted concentrating on three aspects: modelling inputs, modelling methods and pre-processing techniques.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[A comparison between linear correlation analysis and average mutual information is made to find an optimal input technique. For the modelling of the rainfall, a novel hybrid multi-model method is proposed and compared with its constituent models. The models include the artificial neural network, multivariate adaptive regression splines, the k-nearest neighbour, and radial basis support vector regression.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[Each of these methods is applied to model the daily and monthly rainfall, coupled with a pre-processing technique including moving average and principal component analysis.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[In the first stage of the hybrid method, sub-models from each of the above methods are constructed with different parameter settings. In the second stage, the sub-models are ranked with a variable selection technique and the higher ranked models are selected based on the leave-one-out cross-validation error. The forecasting of the hybrid model is performed by the weighted combination of the finally selected models.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Cordón, Oskar - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Kazienko, Przemysław - ed.]]></dc:contributor>
<dc:date><![CDATA[2012]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/58996/AMCS_2012_22_4_5.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/65812/edition/58996/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:58996]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, Volume 22, Number 4 (2012)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=paper&paper=653]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:65812]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
</oai_dc:dc>

</metadata>
	  </record>	</GetRecord>
</OAI-PMH>
