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	<title>zamana bağlı tahmin** **Açıklama:** 1. **derin öğrenme:** Makalenin tem &#8211; BIOENGINEER.ORG</title>
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	<title>zamana bağlı tahmin** **Açıklama:** 1. **derin öğrenme:** Makalenin tem &#8211; BIOENGINEER.ORG</title>
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		<title>Deep Learning Predicts AC Losses in Superconducting Motors</title>
		<link>https://bioengineer.org/deep-learning-predicts-ac-losses-in-superconducting-motors/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Wed, 17 Dec 2025 21:29:58 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[alternatif akım kayıpları]]></category>
		<category><![CDATA[hidrojenle çalışan kriyojenik elektrikli uçaklar]]></category>
		<category><![CDATA[İşte 5 uygun etiket (virgülle ayrılmış): **derin öğrenme]]></category>
		<category><![CDATA[süperiletken tahrik motorları]]></category>
		<category><![CDATA[zamana bağlı tahmin** **Açıklama:** 1. **derin öğrenme:** Makalenin tem]]></category>
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					<description><![CDATA[In a groundbreaking stride towards revolutionizing the aviation industry, a team of researchers has unveiled an advanced deep-learning model capable of temporally predicting the dynamic behavior of AC losses in superconducting propulsion motors. This innovation holds transformative potential for hydrogen-powered cryo-electric aircraft, a next-generation transportation technology aimed at reducing environmental impact while enhancing efficiency and [&#8230;]]]></description>
		
		
		
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