Prediction of drilling rate index from rock strength and cerchar abrasivity index properties using fuzzy inference system
Rock drillability characteristic is one of the important properties for mining and tunneling operations. The rock drillability can be determined by using the drilling rate index (DRI) for engineering applications. The present study attempts to develop a practical and convenient DRI estimation model...
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Veröffentlicht in: | Arabian journal of geosciences 2021-03, Vol.14 (5), Article 354 |
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creator | Sakız, Utku Kaya, Gulhan Ustabas Yaralı, Olgay |
description | Rock drillability characteristic is one of the important properties for mining and tunneling operations. The rock drillability can be determined by using the drilling rate index (DRI) for engineering applications. The present study attempts to develop a practical and convenient DRI estimation model by using rock strength and abrasivity properties. For this purpose, fuzzy inference system (FIS) being an accurate prediction model was applied to predict DRI by using experimental data obtained with 37 different rocks. The predictive FIS based on experts knowledge by taking mechanical and abrasivity properties as input parameters was created on MATLAB. This structure was carried out by using Mamdani extraction method. DRI values obtained experimentally and estimated from the FIS model were compared. This comparison is given with statistically reliable (
R
2
=0.9277) results. In order to prove the validity of the FIS model for DRI prediction, a validation process has been performed by using test data as well. The performance determination coefficients (
R
2
) are found as 0.9513 by using test data. As a result, it was found that DRI values can be predicted very efficiently and accurately with the proposed prediction method. |
doi_str_mv | 10.1007/s12517-021-06647-w |
format | Article |
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R
2
=0.9277) results. In order to prove the validity of the FIS model for DRI prediction, a validation process has been performed by using test data as well. The performance determination coefficients (
R
2
) are found as 0.9513 by using test data. As a result, it was found that DRI values can be predicted very efficiently and accurately with the proposed prediction method.</description><identifier>ISSN: 1866-7511</identifier><identifier>EISSN: 1866-7538</identifier><identifier>DOI: 10.1007/s12517-021-06647-w</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Coefficients ; Drilling ; Drilling rate ; Earth and Environmental Science ; Earth science ; Earth Sciences ; Inference ; Original Paper ; Prediction models ; Predictions ; Properties ; Properties (attributes) ; Rocks</subject><ispartof>Arabian journal of geosciences, 2021-03, Vol.14 (5), Article 354</ispartof><rights>Saudi Society for Geosciences 2021</rights><rights>Saudi Society for Geosciences 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a2931-489af7deaf1a489add5b6f6005d3b23d46c8da1dadd4866bdba77359bb0729b73</citedby><cites>FETCH-LOGICAL-a2931-489af7deaf1a489add5b6f6005d3b23d46c8da1dadd4866bdba77359bb0729b73</cites><orcidid>0000-0002-5643-0531 ; 0000-0003-4965-0330 ; 0000-0002-7246-0714</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/s12517-021-06647-w$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12517-021-06647-w$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Sakız, Utku</creatorcontrib><creatorcontrib>Kaya, Gulhan Ustabas</creatorcontrib><creatorcontrib>Yaralı, Olgay</creatorcontrib><title>Prediction of drilling rate index from rock strength and cerchar abrasivity index properties using fuzzy inference system</title><title>Arabian journal of geosciences</title><addtitle>Arab J Geosci</addtitle><description>Rock drillability characteristic is one of the important properties for mining and tunneling operations. The rock drillability can be determined by using the drilling rate index (DRI) for engineering applications. The present study attempts to develop a practical and convenient DRI estimation model by using rock strength and abrasivity properties. For this purpose, fuzzy inference system (FIS) being an accurate prediction model was applied to predict DRI by using experimental data obtained with 37 different rocks. The predictive FIS based on experts knowledge by taking mechanical and abrasivity properties as input parameters was created on MATLAB. This structure was carried out by using Mamdani extraction method. DRI values obtained experimentally and estimated from the FIS model were compared. This comparison is given with statistically reliable (
R
2
=0.9277) results. In order to prove the validity of the FIS model for DRI prediction, a validation process has been performed by using test data as well. The performance determination coefficients (
R
2
) are found as 0.9513 by using test data. As a result, it was found that DRI values can be predicted very efficiently and accurately with the proposed prediction method.</description><subject>Coefficients</subject><subject>Drilling</subject><subject>Drilling rate</subject><subject>Earth and Environmental Science</subject><subject>Earth science</subject><subject>Earth Sciences</subject><subject>Inference</subject><subject>Original Paper</subject><subject>Prediction models</subject><subject>Predictions</subject><subject>Properties</subject><subject>Properties (attributes)</subject><subject>Rocks</subject><issn>1866-7511</issn><issn>1866-7538</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9UMlOwzAQtRBIlMIPcLLEOWBnsZ0jqtikSnCAs-XEduvSJmXsUNKvxyEV3DjNk94yMw-hS0quKSH8xtO0oDwhKU0IYzlPdkdoQgVjCS8ycfyLKT1FZ96vCGGCcDFB_QsY7erg2ga3Fmtw67VrFhhUMNg12nxhC-0GQ1u_Yx_ANIuwxKrRuDZQLxVgVYHy7tOF_qDfQrs1EJzxuPNDlu32-4G0Jtprg33vg9mcoxOr1t5cHOYUvd3fvc4ek_nzw9Psdp6otMxokotSWa6NslQNWOuiYpYRUuisSjOds1poRXUk8vhjpSvFeVaUVUV4WlY8m6KrMTfe9dEZH-Sq7aCJK2Wal7RklAoRVemoqqH1HoyVW3AbBb2kRA4Vy7FiGSuWPxXLXTRlo8lHcbMw8Bf9j-sbXjWC9w</recordid><startdate>20210301</startdate><enddate>20210301</enddate><creator>Sakız, Utku</creator><creator>Kaya, Gulhan Ustabas</creator><creator>Yaralı, Olgay</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0002-5643-0531</orcidid><orcidid>https://orcid.org/0000-0003-4965-0330</orcidid><orcidid>https://orcid.org/0000-0002-7246-0714</orcidid></search><sort><creationdate>20210301</creationdate><title>Prediction of drilling rate index from rock strength and cerchar abrasivity index properties using fuzzy inference system</title><author>Sakız, Utku ; Kaya, Gulhan Ustabas ; Yaralı, Olgay</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a2931-489af7deaf1a489add5b6f6005d3b23d46c8da1dadd4866bdba77359bb0729b73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Coefficients</topic><topic>Drilling</topic><topic>Drilling rate</topic><topic>Earth and Environmental Science</topic><topic>Earth science</topic><topic>Earth Sciences</topic><topic>Inference</topic><topic>Original Paper</topic><topic>Prediction models</topic><topic>Predictions</topic><topic>Properties</topic><topic>Properties (attributes)</topic><topic>Rocks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sakız, Utku</creatorcontrib><creatorcontrib>Kaya, Gulhan Ustabas</creatorcontrib><creatorcontrib>Yaralı, Olgay</creatorcontrib><collection>CrossRef</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Arabian journal of geosciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sakız, Utku</au><au>Kaya, Gulhan Ustabas</au><au>Yaralı, Olgay</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of drilling rate index from rock strength and cerchar abrasivity index properties using fuzzy inference system</atitle><jtitle>Arabian journal of geosciences</jtitle><stitle>Arab J Geosci</stitle><date>2021-03-01</date><risdate>2021</risdate><volume>14</volume><issue>5</issue><artnum>354</artnum><issn>1866-7511</issn><eissn>1866-7538</eissn><abstract>Rock drillability characteristic is one of the important properties for mining and tunneling operations. The rock drillability can be determined by using the drilling rate index (DRI) for engineering applications. The present study attempts to develop a practical and convenient DRI estimation model by using rock strength and abrasivity properties. For this purpose, fuzzy inference system (FIS) being an accurate prediction model was applied to predict DRI by using experimental data obtained with 37 different rocks. The predictive FIS based on experts knowledge by taking mechanical and abrasivity properties as input parameters was created on MATLAB. This structure was carried out by using Mamdani extraction method. DRI values obtained experimentally and estimated from the FIS model were compared. This comparison is given with statistically reliable (
R
2
=0.9277) results. In order to prove the validity of the FIS model for DRI prediction, a validation process has been performed by using test data as well. The performance determination coefficients (
R
2
) are found as 0.9513 by using test data. As a result, it was found that DRI values can be predicted very efficiently and accurately with the proposed prediction method.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s12517-021-06647-w</doi><orcidid>https://orcid.org/0000-0002-5643-0531</orcidid><orcidid>https://orcid.org/0000-0003-4965-0330</orcidid><orcidid>https://orcid.org/0000-0002-7246-0714</orcidid></addata></record> |
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subjects | Coefficients Drilling Drilling rate Earth and Environmental Science Earth science Earth Sciences Inference Original Paper Prediction models Predictions Properties Properties (attributes) Rocks |
title | Prediction of drilling rate index from rock strength and cerchar abrasivity index properties using fuzzy inference system |
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