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	<title>Smart Cities: Earthquake “Prediction” - Revision history</title>
	<link rel="self" type="application/atom+xml" href="https://dc.ifors.org/index.php?action=history&amp;feed=atom&amp;title=Smart_Cities%3A_Earthquake_%E2%80%9CPrediction%E2%80%9D"/>
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	<updated>2026-06-01T02:23:46Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
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		<id>https://dc.ifors.org/index.php?title=Smart_Cities:_Earthquake_%E2%80%9CPrediction%E2%80%9D&amp;diff=170&amp;oldid=prev</id>
		<title>Dcadmin: Created page with &quot;by: &#039;&#039;&#039;Gerhard -Wilhelm Weber, Fatma Yerlikaya Özkurt, Aysegül Askan&#039;&#039;&#039;  &#039;&#039;&#039;Introduction&#039;&#039;&#039;  In the last decades, learning from data has become very important in every field of science and technology, e.g., in  • computational biology,  • medicine,  • engineering,  • financial sector,  • earth science.  Learning enables for doing estimation and prediction. Regression is mainly based on the ideas of  • least squares estimation  • maximum likelihood estimat...&quot;</title>
		<link rel="alternate" type="text/html" href="https://dc.ifors.org/index.php?title=Smart_Cities:_Earthquake_%E2%80%9CPrediction%E2%80%9D&amp;diff=170&amp;oldid=prev"/>
		<updated>2026-05-11T05:10:11Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;by: &amp;#039;&amp;#039;&amp;#039;Gerhard -Wilhelm Weber, Fatma Yerlikaya Özkurt, Aysegül Askan&amp;#039;&amp;#039;&amp;#039;  &amp;#039;&amp;#039;&amp;#039;Introduction&amp;#039;&amp;#039;&amp;#039;  In the last decades, learning from data has become very important in every field of science and technology, e.g., in  • computational biology,  • medicine,  • engineering,  • financial sector,  • earth science.  Learning enables for doing estimation and prediction. Regression is mainly based on the ideas of  • least squares estimation  • maximum likelihood estimat...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;by: &amp;#039;&amp;#039;&amp;#039;Gerhard -Wilhelm Weber, Fatma Yerlikaya Özkurt, Aysegül Askan&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
&lt;br /&gt;
&amp;#039;&amp;#039;&amp;#039;Introduction&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
&lt;br /&gt;
In the last decades, learning from data has become very important in every field of science and technology, e.g., in&lt;br /&gt;
&lt;br /&gt;
• computational biology,&lt;br /&gt;
&lt;br /&gt;
• medicine,&lt;br /&gt;
&lt;br /&gt;
• engineering,&lt;br /&gt;
&lt;br /&gt;
• financial sector,&lt;br /&gt;
&lt;br /&gt;
• earth science.&lt;br /&gt;
&lt;br /&gt;
Learning enables for doing estimation and prediction. Regression is mainly based on the ideas of&lt;br /&gt;
&lt;br /&gt;
• least squares estimation&lt;br /&gt;
&lt;br /&gt;
• maximum likelihood estimation&lt;br /&gt;
&lt;br /&gt;
• and classification.&lt;br /&gt;
&lt;br /&gt;
New tools for data analysis, based on nonparametric regression or smoothing:&lt;br /&gt;
&lt;br /&gt;
• CMARS method: an alternative approach to the well-known data mining tool MARS.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
Link to material: http://ifors.org/wp-content/uploads/2016/11/Aveiro-2016-Earthquakes.pdf&lt;br /&gt;
&lt;br /&gt;
[[Category: Safety]]&lt;/div&gt;</summary>
		<author><name>Dcadmin</name></author>
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