Evaluation of capability of blast-induced ground vibration predictors considering measurement distance and different error measures
This study aims to investigate capability of the vibration prediction approaches, comprehensively. Field investigations were performed in a sandstone quarry. All the main conventional scaled distance equations were evaluated. A multivariate equation that contains blast design parameters was created...
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| Veröffentlicht in: | Environmental earth sciences 2019-07, Vol.78 (14), p.1-17, Article 421 |
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| creator | Hudaverdi, Turker Akyildiz, Ozge |
| description | This study aims to investigate capability of the vibration prediction approaches, comprehensively. Field investigations were performed in a sandstone quarry. All the main conventional scaled distance equations were evaluated. A multivariate equation that contains blast design parameters was created by stepwise regression. A robust artificial neural network model was constructed. Effect of the additional parameters on success of the vibration estimation was examined. The success of the equations was evaluated considering the measurement distance. Evaluation of vibrations based on the measurement distance provided an opportunity to examine effectiveness of the equations that contains inelastic attenuation factor. Suitable error measures were investigated to examine the precision of vibration estimation. Both percentage errors and symmetric errors were found to be useful. Increase in the measurement distance was resulted in increase in prediction error. The classical scaled distance equations were found to be quite successful. The multivariate equation and artificial neural network model did not made better predictions than the scaled distance equations for long distance. The equations with inelastic attenuation formula do not have any advantage over classical scaled distance equations. |
| doi_str_mv | 10.1007/s12665-019-8427-5 |
| format | Article |
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Field investigations were performed in a sandstone quarry. All the main conventional scaled distance equations were evaluated. A multivariate equation that contains blast design parameters was created by stepwise regression. A robust artificial neural network model was constructed. Effect of the additional parameters on success of the vibration estimation was examined. The success of the equations was evaluated considering the measurement distance. Evaluation of vibrations based on the measurement distance provided an opportunity to examine effectiveness of the equations that contains inelastic attenuation factor. Suitable error measures were investigated to examine the precision of vibration estimation. Both percentage errors and symmetric errors were found to be useful. Increase in the measurement distance was resulted in increase in prediction error. The classical scaled distance equations were found to be quite successful. The multivariate equation and artificial neural network model did not made better predictions than the scaled distance equations for long distance. The equations with inelastic attenuation formula do not have any advantage over classical scaled distance equations.</description><identifier>ISSN: 1866-6280</identifier><identifier>EISSN: 1866-6299</identifier><identifier>DOI: 10.1007/s12665-019-8427-5</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Artificial neural networks ; Attenuation ; Biogeosciences ; Design parameters ; Distance ; Earth and Environmental Science ; Earth Sciences ; Environmental Science and Engineering ; Error analysis ; Errors ; Evaluation ; Field investigations ; Field tests ; Geochemistry ; Geology ; Ground motion ; Hydrology/Water Resources ; Investigations ; Mathematical models ; Measurement ; Multivariate analysis ; Neural networks ; Original Article ; Parameter estimation ; Parameters ; Quarries ; Robustness (mathematics) ; Sandstone ; Sedimentary rocks ; Terrestrial Pollution ; Vibration ; Vibration measurement ; Vibrations</subject><ispartof>Environmental earth sciences, 2019-07, Vol.78 (14), p.1-17, Article 421</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2019</rights><rights>Environmental Earth Sciences is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a339t-a946f2cf757148d139b1d5cdbfb2f3d249c25dd2403ea1c8438d9c72a5c603513</citedby><cites>FETCH-LOGICAL-a339t-a946f2cf757148d139b1d5cdbfb2f3d249c25dd2403ea1c8438d9c72a5c603513</cites><orcidid>0000-0002-5538-4211 ; 0000-0002-9326-9935</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12665-019-8427-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12665-019-8427-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51298</link.rule.ids></links><search><creatorcontrib>Hudaverdi, Turker</creatorcontrib><creatorcontrib>Akyildiz, Ozge</creatorcontrib><title>Evaluation of capability of blast-induced ground vibration predictors considering measurement distance and different error measures</title><title>Environmental earth sciences</title><addtitle>Environ Earth Sci</addtitle><description>This study aims to investigate capability of the vibration prediction approaches, comprehensively. Field investigations were performed in a sandstone quarry. All the main conventional scaled distance equations were evaluated. A multivariate equation that contains blast design parameters was created by stepwise regression. A robust artificial neural network model was constructed. Effect of the additional parameters on success of the vibration estimation was examined. The success of the equations was evaluated considering the measurement distance. Evaluation of vibrations based on the measurement distance provided an opportunity to examine effectiveness of the equations that contains inelastic attenuation factor. Suitable error measures were investigated to examine the precision of vibration estimation. Both percentage errors and symmetric errors were found to be useful. Increase in the measurement distance was resulted in increase in prediction error. The classical scaled distance equations were found to be quite successful. The multivariate equation and artificial neural network model did not made better predictions than the scaled distance equations for long distance. The equations with inelastic attenuation formula do not have any advantage over classical scaled distance equations.</description><subject>Artificial neural networks</subject><subject>Attenuation</subject><subject>Biogeosciences</subject><subject>Design parameters</subject><subject>Distance</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Environmental Science and Engineering</subject><subject>Error analysis</subject><subject>Errors</subject><subject>Evaluation</subject><subject>Field investigations</subject><subject>Field tests</subject><subject>Geochemistry</subject><subject>Geology</subject><subject>Ground motion</subject><subject>Hydrology/Water Resources</subject><subject>Investigations</subject><subject>Mathematical models</subject><subject>Measurement</subject><subject>Multivariate analysis</subject><subject>Neural networks</subject><subject>Original Article</subject><subject>Parameter estimation</subject><subject>Parameters</subject><subject>Quarries</subject><subject>Robustness (mathematics)</subject><subject>Sandstone</subject><subject>Sedimentary rocks</subject><subject>Terrestrial Pollution</subject><subject>Vibration</subject><subject>Vibration measurement</subject><subject>Vibrations</subject><issn>1866-6280</issn><issn>1866-6299</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kMlqwzAQhk1poSHNA_Qm6FmtFku2jiWkCxR6ac9C1hIUEssd2YGc--K1cZdT5zIL_z_DfEVxTcktJaS6y5RJKTChCtclq7A4Kxa0lhJLptT5b12Ty2KV846MwSlXRC6Kz83R7AfTx9SiFJA1nWniPvanqWv2Jvc4tm6w3qEtpKF16BgbmPUdeBdtnyAjm9ocnYfYbtHBmzyAP_i2Ry7m3rTWIzM6XQzBwzT2AAl-hPmquAhmn_3qOy-L94fN2_oJv7w-Pq_vX7DhXPXYqFIGZkMlKlrWbnygoU5Y14SGBe5YqSwTbsyEe0NtXfLaKVsxI6wkXFC-LG7mvR2kj8HnXu_SAO14UjMmFKO0ZOWoorPKQsoZfNAdxIOBk6ZET7j1jFuPuPWEW4vRw2ZP7iYEHv42_2_6Aqv8hag</recordid><startdate>20190701</startdate><enddate>20190701</enddate><creator>Hudaverdi, Turker</creator><creator>Akyildiz, Ozge</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>M2P</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0002-5538-4211</orcidid><orcidid>https://orcid.org/0000-0002-9326-9935</orcidid></search><sort><creationdate>20190701</creationdate><title>Evaluation of capability of blast-induced ground vibration predictors considering measurement distance and different error measures</title><author>Hudaverdi, Turker ; Akyildiz, Ozge</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a339t-a946f2cf757148d139b1d5cdbfb2f3d249c25dd2403ea1c8438d9c72a5c603513</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Artificial neural networks</topic><topic>Attenuation</topic><topic>Biogeosciences</topic><topic>Design parameters</topic><topic>Distance</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Environmental Science and Engineering</topic><topic>Error analysis</topic><topic>Errors</topic><topic>Evaluation</topic><topic>Field investigations</topic><topic>Field tests</topic><topic>Geochemistry</topic><topic>Geology</topic><topic>Ground motion</topic><topic>Hydrology/Water Resources</topic><topic>Investigations</topic><topic>Mathematical models</topic><topic>Measurement</topic><topic>Multivariate analysis</topic><topic>Neural networks</topic><topic>Original Article</topic><topic>Parameter estimation</topic><topic>Parameters</topic><topic>Quarries</topic><topic>Robustness (mathematics)</topic><topic>Sandstone</topic><topic>Sedimentary rocks</topic><topic>Terrestrial Pollution</topic><topic>Vibration</topic><topic>Vibration measurement</topic><topic>Vibrations</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hudaverdi, Turker</creatorcontrib><creatorcontrib>Akyildiz, Ozge</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Science Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><jtitle>Environmental earth sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hudaverdi, Turker</au><au>Akyildiz, Ozge</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of capability of blast-induced ground vibration predictors considering measurement distance and different error measures</atitle><jtitle>Environmental earth sciences</jtitle><stitle>Environ Earth Sci</stitle><date>2019-07-01</date><risdate>2019</risdate><volume>78</volume><issue>14</issue><spage>1</spage><epage>17</epage><pages>1-17</pages><artnum>421</artnum><issn>1866-6280</issn><eissn>1866-6299</eissn><abstract>This study aims to investigate capability of the vibration prediction approaches, comprehensively. Field investigations were performed in a sandstone quarry. All the main conventional scaled distance equations were evaluated. A multivariate equation that contains blast design parameters was created by stepwise regression. A robust artificial neural network model was constructed. Effect of the additional parameters on success of the vibration estimation was examined. The success of the equations was evaluated considering the measurement distance. Evaluation of vibrations based on the measurement distance provided an opportunity to examine effectiveness of the equations that contains inelastic attenuation factor. Suitable error measures were investigated to examine the precision of vibration estimation. Both percentage errors and symmetric errors were found to be useful. Increase in the measurement distance was resulted in increase in prediction error. The classical scaled distance equations were found to be quite successful. The multivariate equation and artificial neural network model did not made better predictions than the scaled distance equations for long distance. The equations with inelastic attenuation formula do not have any advantage over classical scaled distance equations.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s12665-019-8427-5</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0002-5538-4211</orcidid><orcidid>https://orcid.org/0000-0002-9326-9935</orcidid></addata></record> |
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| subjects | Artificial neural networks Attenuation Biogeosciences Design parameters Distance Earth and Environmental Science Earth Sciences Environmental Science and Engineering Error analysis Errors Evaluation Field investigations Field tests Geochemistry Geology Ground motion Hydrology/Water Resources Investigations Mathematical models Measurement Multivariate analysis Neural networks Original Article Parameter estimation Parameters Quarries Robustness (mathematics) Sandstone Sedimentary rocks Terrestrial Pollution Vibration Vibration measurement Vibrations |
| title | Evaluation of capability of blast-induced ground vibration predictors considering measurement distance and different error measures |
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