<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Bouc–Wen model &#8211; BIOENGINEER.ORG</title>
	<atom:link href="https://bioengineer.org/tag/bouc-wen-model/feed/" rel="self" type="application/rss+xml" />
	<link>https://bioengineer.org</link>
	<description>Bioengineering</description>
	<lastBuildDate>Sat, 24 Oct 2026 10:26:35 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.1.3</generator>

<image>
	<url>https://bioengineer.org/wp-content/uploads/2019/09/cropped-bioengineering-32x32.png</url>
	<title>Bouc–Wen model &#8211; BIOENGINEER.ORG</title>
	<link>https://bioengineer.org</link>
	<width>32</width>
	<height>32</height>
</image> 
<site xmlns="com-wordpress:feed-additions:1">72741379</site>	<item>
		<title>Physics Meets Machine Learning to Predict the Full Seismic Response of Steel–Concrete Composite Structures</title>
		<link>https://bioengineer.org/physics-meets-machine-learning-to-predict-the-full-seismic-response-of-steel-concrete-composite-structures/</link>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Sat, 24 Oct 2026 10:26:35 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Bouc–Wen model]]></category>
		<category><![CDATA[energy dissipation]]></category>
		<category><![CDATA[hysteresis]]></category>
		<category><![CDATA[LSTM]]></category>
		<category><![CDATA[Neural Networks]]></category>
		<category><![CDATA[Physics-Informed Machine Learning]]></category>
		<category><![CDATA[prefabricated structures]]></category>
		<category><![CDATA[seismic performance]]></category>
		<category><![CDATA[small-sample learning]]></category>
		<category><![CDATA[steel–concrete composite structures]]></category>
		<category><![CDATA[stiffness degradation]]></category>
		<category><![CDATA[structural engineering]]></category>
		<guid isPermaLink="false">https://bioengineer.org/?p=451599</guid>

					<description><![CDATA[A new physics-informed machine learning framework embeds hysteretic mechanical laws into neural network training, reproducing full seismic load–deformation and energy dissipation behavior of steel frames and composite walls with R² values above 0.90 from limited test data.]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">451599</post-id>	</item>
	</channel>
</rss>
