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		<title>Monotonic neural networks reveal building water pipes are drastically oversized</title>
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		<pubDate>Mon, 05 Oct 2026 04:58:26 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[building services engineering]]></category>
		<category><![CDATA[building water supply]]></category>
		<category><![CDATA[differential evolution]]></category>
		<category><![CDATA[fixture use probability]]></category>
		<category><![CDATA[Hunter's method]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[monotonic neural networks]]></category>
		<category><![CDATA[plumbing design codes]]></category>
		<category><![CDATA[SHAP interpretability]]></category>
		<category><![CDATA[simultaneous peak water flow]]></category>
		<category><![CDATA[TensorFlow Lattice]]></category>
		<category><![CDATA[water conservation]]></category>
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					<description><![CDATA[Researchers used monotonic neural networks to show that designing residential water systems at the 98th rather than the 99th percentile can cut peak flow estimates by up to 87 percent compared with building codes.]]></description>
		
		
		
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