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	<title>AI in Energy Storage &#8211; BIOENGINEER.ORG</title>
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		<title>Next-Gen Neural Network Optimizes Lithium-Ion Battery Health</title>
		<link>https://bioengineer.org/next-gen-neural-network-optimizes-lithium-ion-battery-health/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Tue, 18 Nov 2025 16:41:34 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[**Etiketler:** Northern Goshawk Optimization]]></category>
		<category><![CDATA[AI battery monitoring]]></category>
		<category><![CDATA[AI in Energy Storage]]></category>
		<category><![CDATA[Hybrid Neural Network]]></category>
		<category><![CDATA[İşte 5 uygun etiket: **lithium-ion battery health]]></category>
		<category><![CDATA[Lithium-Ion Battery Health]]></category>
		<category><![CDATA[lityum-iyon pillerin sağlık durumunun tahmini. 2. **Northern Goshawk Optimization (Kuzey Şahini Optim]]></category>
		<category><![CDATA[Northern Goshawk Optimization]]></category>
		<category><![CDATA[Predictive Maintenance]]></category>
		<category><![CDATA[predictive maintenance** **Açıklama:** 1. **lithium-ion battery health:** Makalenin temel konusu]]></category>
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					<description><![CDATA[In a groundbreaking development within the field of battery technology, researchers have unveiled a cutting-edge model that promises to significantly enhance the accuracy of state of health estimation for lithium-ion batteries. This innovative approach combines the principles of a novel algorithm known as the Northern Goshawk Optimization (NGO) with a hybrid neural network architecture. The [&#8230;]]]></description>
		
		
		
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