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		<title>Neural Network Predictive Control Cuts Building Energy Use While Boosting Comfort</title>
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		<pubDate>Mon, 19 Oct 2026 06:27:46 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[building energy efficiency]]></category>
		<category><![CDATA[daylighting]]></category>
		<category><![CDATA[GA-BP neural network]]></category>
		<category><![CDATA[life cycle cost]]></category>
		<category><![CDATA[model predictive control]]></category>
		<category><![CDATA[MOPSO]]></category>
		<category><![CDATA[Multi-objective optimization]]></category>
		<category><![CDATA[NNMPC]]></category>
		<category><![CDATA[NSGA-II]]></category>
		<category><![CDATA[sensor-based control]]></category>
		<category><![CDATA[smart buildings]]></category>
		<category><![CDATA[thermal comfort]]></category>
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					<description><![CDATA[A neural network predictive control framework that jointly optimizes thermal comfort, daylighting, energy use, and life-cycle cost cut a school building's energy consumption by 17.4 percent while raising user satisfaction from 68.2 to 86.3 percent.]]></description>
		
		
		
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