https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Entezari%2A_et_al_2024a Entezari* et al 2024a - Revision history 2026-05-11T12:48:47Z Revision history for this page on the wiki MediaWiki 1.27.0-wmf.10 https://www.scipedia.com/wd/index.php?title=Entezari*_et_al_2024a&diff=301143&oldid=prev JSanchez: JSanchez moved page Draft Sanchez Pinedo 265486384 to Entezari* et al 2024a 2024-06-06T13:38:44Z <p>JSanchez moved page <a href="/public/Draft_Sanchez_Pinedo_265486384" class="mw-redirect" title="Draft Sanchez Pinedo 265486384">Draft Sanchez Pinedo 265486384</a> to <a href="/public/Entezari*_et_al_2024a" title="Entezari* et al 2024a">Entezari* et al 2024a</a></p> <table class="diff diff-contentalign-left" data-mw="interface"> <tr style='vertical-align: top;' lang='en'> <td colspan='1' style="background-color: white; color:black; text-align: center;">← Older revision</td> <td colspan='1' style="background-color: white; color:black; text-align: center;">Revision as of 13:38, 6 June 2024</td> </tr><tr><td colspan='2' style='text-align: center;' lang='en'><div class="mw-diff-empty">(No difference)</div> </td></tr></table> JSanchez https://www.scipedia.com/wd/index.php?title=Entezari*_et_al_2024a&diff=301142&oldid=prev JSanchez at 13:38, 6 June 2024 2024-06-06T13:38:38Z <p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class='diff-marker' /> <col class='diff-content' /> <col class='diff-marker' /> <col class='diff-content' /> <tr style='vertical-align: top;' lang='en'> <td colspan='2' style="background-color: white; color:black; text-align: center;">← Older revision</td> <td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 13:38, 6 June 2024</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l3" >Line 3:</td> <td colspan="2" class="diff-lineno">Line 3:</td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>This paper is an extension of our previous research investigating the potential of machine learning models to estimate shear wave velocity (Vs) from piezocone penetration test (CPTu) measurements. The aim of this update is to examine the effect of incorporating geographical information, namely latitude and longitude, as input parameters to the machine learning models. New models are developed by incorporating both CPTu parameters and spatial coordinates as input features and are compared to models developed with only CPTu parameters. Furthermore, SHAP (SHapley Additive exPlanations) analysis is employed to assess the importance of different features and variables in the developed machine learning models. The results show improvement in prediction performance when adding geographical data, indicating the influence of geological variations on Vs. The paper shows the potential of using geospatial information to improve the data-driven approach for estimating soil properties from CPTu tests when large worldwide datasets are available.</div></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>This paper is an extension of our previous research investigating the potential of machine learning models to estimate shear wave velocity (Vs) from piezocone penetration test (CPTu) measurements. The aim of this update is to examine the effect of incorporating geographical information, namely latitude and longitude, as input parameters to the machine learning models. New models are developed by incorporating both CPTu parameters and spatial coordinates as input features and are compared to models developed with only CPTu parameters. Furthermore, SHAP (SHapley Additive exPlanations) analysis is employed to assess the importance of different features and variables in the developed machine learning models. The results show improvement in prediction performance when adding geographical data, indicating the influence of geological variations on Vs. The paper shows the potential of using geospatial information to improve the data-driven approach for estimating soil properties from CPTu tests when large worldwide datasets are available.</div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">== Full Paper ==</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">&lt;pdf&gt;Media:Draft_Sanchez Pinedo_26548638480.pdf&lt;/pdf&gt;</ins></div></td></tr> </table> JSanchez https://www.scipedia.com/wd/index.php?title=Entezari*_et_al_2024a&diff=301140&oldid=prev JSanchez at 13:38, 6 June 2024 2024-06-06T13:38:37Z <p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class='diff-marker' /> <col class='diff-content' /> <col class='diff-marker' /> <col class='diff-content' /> <tr style='vertical-align: top;' lang='en'> <td colspan='2' style="background-color: white; color:black; text-align: center;">← Older revision</td> <td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 13:38, 6 June 2024</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1" >Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">&#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; </ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==Abstract==</ins></div></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">This paper is an extension of our previous research investigating the potential of machine learning models to estimate shear wave velocity (Vs) from piezocone penetration test (CPTu) measurements. The aim of this update is to examine the effect of incorporating geographical information, namely latitude and longitude, as input parameters to the machine learning models. New models are developed by incorporating both CPTu parameters and spatial coordinates as input features and are compared to models developed with only CPTu parameters. Furthermore, SHAP (SHapley Additive exPlanations) analysis is employed to assess the importance of different features and variables in the developed machine learning models. The results show improvement in prediction performance when adding geographical data, indicating the influence of geological variations on Vs. The paper shows the potential of using geospatial information to improve the data-driven approach for estimating soil properties from CPTu tests when large worldwide datasets are available.</ins></div></td></tr> </table> JSanchez https://www.scipedia.com/wd/index.php?title=Entezari*_et_al_2024a&diff=301139&oldid=prev JSanchez: Created blank page 2024-06-06T13:38:35Z <p>Created blank page</p> <p><b>New page</b></p><div></div> JSanchez