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	<title>multi-criteria decision analysis hydrology &#8211; BIOENGINEER.ORG</title>
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		<title>Machine Learning Enhances Flood Risk Assessment in Jiangxi</title>
		<link>https://bioengineer.org/machine-learning-enhances-flood-risk-assessment-in-jiangxi/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Mon, 13 Oct 2025 15:56:19 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[climate change adaptation strategies]]></category>
		<category><![CDATA[data-driven disaster preparedness]]></category>
		<category><![CDATA[Jiangxi Province flood prediction]]></category>
		<category><![CDATA[machine learning flood risk assessment]]></category>
		<category><![CDATA[multi-criteria decision analysis hydrology]]></category>
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					<description><![CDATA[In a groundbreaking advancement that could revolutionize natural disaster preparedness, researchers have developed an innovative flood risk assessment framework that synergizes machine learning techniques with multi-criteria decision analysis (MCDA) to address the complex hydrological challenges in Jiangxi Province, China. This pioneering approach not only sharpens the accuracy of flood hazard predictions but also offers nuanced [&#8230;]]]></description>
		
		
		
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