<?xml version="1.0" encoding="UTF-8"?><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>2026-10-23T14:58:25Z</responseDate><request verb="GetRecord" identifier="oai:gumushane-rdlopen.rawdatalibrary.net:gumushane/13291" metadataPrefix="oai_dc">https://gumushane-rdlopen.rawdatalibrary.net/oai/request</request><GetRecord><record><header><identifier>oai:gumushane-rdlopen.rawdatalibrary.net:gumushane/13291</identifier><datestamp>2026-10-22T11:36:10Z</datestamp><setSpec>openaire</setSpec><setSpec>driver</setSpec><setSpec>com_gumushane_10000</setSpec><setSpec>col_gumushane_10001</setSpec><setSpec>com_gumushane_10007</setSpec><setSpec>col_gumushane_10171</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" 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>Wong-Zakai Method for Stochastic Differential Equations in Engineering</dc:title><dc:creator>Sengul, Suleyman</dc:creator><dc:creator>Bekiryazici, Zafer</dc:creator><dc:creator>Merdan, Mehmet</dc:creator><dc:subject>Brownian motion</dc:subject><dc:subject>Euler-Maruyama method</dc:subject><dc:subject>Milstein method</dc:subject><dc:subject>solar irradiance</dc:subject><dc:subject>stochastic differential equation</dc:subject><dc:subject>Wong-Zakai approximation</dc:subject><dc:description>In this paper, Wong-Zakai approximation methods are presented for some stochastic differential equations in engineering sciences. Wong-Zakai approximate solutions of the equations are analyzed and the numerical results are compared with results from popular approximation schemes for stochastic differential equations such as Euler-Maruyama and Milstein methods. Several differential equations from engineering problems containing stochastic noise are investigated as numerical examples. Results show that Wong-Zakai method is a reliable tool for studying stochastic differential equations and can be used as an alternative for the known approximation techniques for stochastic models.</dc:description><dc:publisher>Serbian Society of Heat Transfer Engineers</dc:publisher><dc:date>2021</dc:date><dc:type>Article</dc:type><dc:identifier>https://rdlopen.rawdatalibrary.net/r/gumushane/13291</dc:identifier><dc:identifier>https://doi.org/10.2298/tsci200528014s</dc:identifier><dc:identifier>0354-9836</dc:identifier><dc:language>en</dc:language><dc:relation>Thermal Science</dc:relation><dc:rights>info:eu-repo/semantics/openAccess</dc:rights><dc:type>info:eu-repo/semantics/article</dc:type><dc:identifier>https://gumushane-rdlopen.rawdatalibrary.net/tr/items/gumushane/13291</dc:identifier></oai_dc:dc></metadata></record></GetRecord></OAI-PMH>