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	<title>Fuzzy System Archives &#8212; MATLAB Number ONE</title>
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	<title>Fuzzy System Archives &#8212; MATLAB Number ONE</title>
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		<title>12 MATLAB code examples of fuzzy logic and ANFIS</title>
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		<pubDate>Fri, 08 Jul 2022 15:34:32 +0000</pubDate>
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					<description><![CDATA[<p>One of the ways to learn programming and create fuzzy and neuro-fuzzy systems in MATLAB is to use projects and examples where you can see all the commands of a section one after the other. We have prepared 12 MATLAB code samples for you. Subjects of the codes: Estimating the rank of PhD students based [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/12-matlab-code-examples-of-fuzzy-logic-and-anfis/">12 MATLAB code examples of fuzzy logic and ANFIS</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Upper range value for the variable must be greater than the lower range</title>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 14 Sep 2020 03:13:43 +0000</pubDate>
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					<description><![CDATA[<p>There is an error in ANFIS in MATLAB.  In this tutorial, you get familiar with solving this error in MATLAB. &#160; &#8220;Error: Upper range value for the variable must be greater than the lower range&#8221;. &#160; &#160; This error happens when you want to use genfis function in MATLAB. Error using fisvar/set.Range (line 218) Upper [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/upper-range-value-for-the-variable-must-be-greater-than-the-lower-range/">Upper range value for the variable must be greater than the lower range</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Neuro-Fuzzy (ANFIS) in MATLAB</title>
		<link>https://matlab1.com/shop/matlab-video/neuro-fuzzy-anfis-in-matlab/</link>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 03 Aug 2020 11:25:59 +0000</pubDate>
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					<description><![CDATA[<p>ANFIS (adaptive network-based fuzzy inference system) is an adaptable and educational network that is quite similar in function to the fuzzy inference system. To create an optimal fuzzy system based on input and output data sets, use ANFIS in the Fuzzy toolbox. As we know, fuzzy-neural methods, using the advantages of both fuzzy and neural [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-video/neuro-fuzzy-anfis-in-matlab/">Neuro-Fuzzy (ANFIS) in MATLAB</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Fuzzy system in MATLAB</title>
		<link>https://matlab1.com/shop/matlab-video/fuzzy-system-in-matlab/</link>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 03 Aug 2020 07:55:33 +0000</pubDate>
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					<description><![CDATA[<p>The theory of fuzzy sets was proposed in 1965 by Professor Lotfi Asgarzadeh, an Iranian scientist and professor at Berkeley University in the United States. The word fuzzy in the Oxford Dictionary is defined vaguely, vaguely, and inaccurately. Using this model is suitable for when the data is vague, uncertain, and inaccurate. Fuzzy theory includes [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-video/fuzzy-system-in-matlab/">Fuzzy system in MATLAB</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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