Prediction of the performance of impact hammer by adaptive neuro-fuzzy inference system modelling

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dc.authoridÖZACAR, Vehbi/0000-0002-5842-8777
dc.authoridAksoy, Cemalettin Okay/0000-0002-4328-4862
dc.authoridOnargan, Turgay/0000-0003-3949-2594
dc.authoridKUCUK, Kerim/0000-0002-1921-5429
dc.authoridBasarir, Hakan/0000-0003-4556-4953
dc.authorwosidÖZACAR, Vehbi/Q-1620-2019
dc.authorwosidGENIS, MELIH/JWO-5567-2024
dc.authorwosidAksoy, Cemalettin Okay/P-5395-2019
dc.authorwosidOnargan, Turgay/P-2165-2019
dc.authorwosidKUCUK, Kerim/P-2217-2019
dc.authorwosidBasarir, Hakan/C-2237-2014
dc.contributor.authorKucuk, K.
dc.contributor.authorAksoy, C. O.
dc.contributor.authorBasarir, H.
dc.contributor.authorOnargan, T.
dc.contributor.authorGenis, M.
dc.contributor.authorOzacar, V.
dc.date.accessioned2024-08-04T20:32:35Z
dc.date.available2024-08-04T20:32:35Z
dc.date.issued2011
dc.departmentİnönü Üniversitesien_US
dc.description.abstractImpact type excavators are widely used for excavations, performed in weak-laminated-foliated-anisotropic rocks. Therefore the prediction of the performance of impact hammer is very important in many mining and civil engineering projects. This paper describes the construction of adaptive neuro-fuzzy inference system model for predicting the performance of impact hammer type excavator by considering rock and excavating machine properties such as block punch strength index, geological strength index system and impact hammer power. Extensive field and laboratory studies were conducted in the tunnel construction route of the second stage of Izmir Metro Project, which excavated in laminated-foliated flysch rocks. The results of the constructed adaptive neuro-fuzzy inference system and traditional multiple regression models were compared. Although the prediction performance of traditional multiple regression model is high, it is seen that adaptive neuro-fuzzy inference model exhibits better prediction performance according to statistical performance indicators. By means of the developed model, the performance of impact type excavators can be predicted in terms of net excavation based on the selected rock and machine properties. (C) 2010 Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipTUBITAK (The Scientific and Technological Research Council of Turkey) [108M151]; Dokuz Eylul University of Scientific Research Bureau [2005384]en_US
dc.description.sponsorshipSome part of the this study was conducted under the scientific project numbered 108M151 of TUBITAK (The Scientific and Technological Research Council of Turkey) and 2005384 of Dokuz Eylul University of Scientific Research Bureau, and the protocol made with Bozoglu Construction Inc. The authors would like to thanks Izmir Greater Municipality, Metin ERIS and Levent NURAY from STFA (consulting firm), Mustafa ATTAROGLU and Yalcin YILMAZ from BOZOGLU GROUP Construction Inc. for their collaboration.en_US
dc.identifier.doi10.1016/j.tust.2010.06.011
dc.identifier.endpage45en_US
dc.identifier.issn0886-7798
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-78349306944en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage38en_US
dc.identifier.urihttps://doi.org/10.1016/j.tust.2010.06.011
dc.identifier.urihttps://hdl.handle.net/11616/95180
dc.identifier.volume26en_US
dc.identifier.wosWOS:000285231600005en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofTunnelling and Underground Space Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectImpact hammeren_US
dc.subjectBlock punch strength indexen_US
dc.subjectNet excavationen_US
dc.subjectMultiple regression modellingen_US
dc.subjectAdaptive neuro-fuzzy inference system modellingen_US
dc.titlePrediction of the performance of impact hammer by adaptive neuro-fuzzy inference system modellingen_US
dc.typeArticleen_US

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