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		<title>Weight normalization keeps interval type-2 fuzzy uncertainty bounded</title>
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		<pubDate>Mon, 26 Oct 2026 22:34:06 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Algebraic]]></category>
		<category><![CDATA[autoregressive inputs]]></category>
		<category><![CDATA[clinical risk assessment]]></category>
		<category><![CDATA[fuzzy aggregation]]></category>
		<category><![CDATA[industrial fault detection]]></category>
		<category><![CDATA[interval type-2 fuzzy sets]]></category>
		<category><![CDATA[Mamdani inference]]></category>
		<category><![CDATA[multi-criteria decision-making]]></category>
		<category><![CDATA[uncertainty quantification]]></category>
		<category><![CDATA[weight normalization]]></category>
		<category><![CDATA[width]]></category>
		<category><![CDATA[width certificates]]></category>
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					<description><![CDATA[A theoretical and computational study identifies normalized weights as the condition that keeps interval type-2 fuzzy aggregation uncertainty bounded as decision criteria accumulate.]]></description>
		
		
		
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