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	<title>reliability analysis &#8211; BIOENGINEER.ORG</title>
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		<title>AI Framework Designs Fly Ash Geopolymer Concrete Balancing Strength, Cost and CO2</title>
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		<pubDate>Sat, 24 Oct 2026 04:08:17 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[CatBoost]]></category>
		<category><![CDATA[compressive strength]]></category>
		<category><![CDATA[CTGAN]]></category>
		<category><![CDATA[data augmentation]]></category>
		<category><![CDATA[fly ash geopolymer concrete]]></category>
		<category><![CDATA[Gaussian Process Regression]]></category>
		<category><![CDATA[low-carbon concrete]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Multi-objective optimization]]></category>
		<category><![CDATA[reliability analysis]]></category>
		<category><![CDATA[SHAP explainability]]></category>
		<category><![CDATA[sustainable construction]]></category>
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					<description><![CDATA[A new study combines CTGAN-generated synthetic data, hybrid machine learning, SHAP explainability, reliability analysis and multi-objective optimization to design fly ash geopolymer concrete mixtures that cut cost and carbon emissions with minimal strength loss, pending laboratory validation.]]></description>
		
		
		
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