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

Impact 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. © 2010 Elsevier Ltd.

Dergi Adı Tunnelling and Underground Space Technology
Dergi Cilt Bilgisi 26
Dergi Sayısı 1
Sayfalar 38 - 45
Yayın Yılı 2011
Eser Adı
[dc.title]
Prediction of the performance of impact hammer by adaptive neuro-fuzzy inference system modelling
Yazar
[dc.contributor.author]
Kucuk K.
Yazar
[dc.contributor.author]
Aksoy C.O.
Yazar
[dc.contributor.author]
Basarir H.
Yazar
[dc.contributor.author]
Onargan T.
Yazar
[dc.contributor.author]
Genis M.
Yazar
[dc.contributor.author]
Ozacar V.
Yayın Yılı
[dc.date.issued]
2011
Yayın Türü
[dc.type]
article
Özet
[dc.description.abstract]
Impact 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. © 2010 Elsevier Ltd.
Kayıt Giriş Tarihi
[dc.date.accessioned]
2019-12-23
Açık Erişim Tarihi
[dc.date.available]
2019-12-23
Yayın Dili
[dc.language.iso]
eng
Konu Başlıkları
[dc.subject]
Adaptive neuro-fuzzy inference system modelling
Konu Başlıkları
[dc.subject]
Block punch strength index
Konu Başlıkları
[dc.subject]
Impact hammer
Konu Başlıkları
[dc.subject]
Multiple regression modelling
Konu Başlıkları
[dc.subject]
Net excavation
Haklar
[dc.rights]
info:eu-repo/semantics/closedAccess
ISSN
[dc.identifier.issn]
0886-7798
Sponsor YAYINCI
[dc.description.sponsorship]
2005384
Sponsor YAYINCI
[dc.description.sponsorship]
Some 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 Bozoğlu Construction Inc. The authors would like to thanks Izmir Greater Municipality, Metin ERIS and Levent NURAY from STFA (consulting firm), Mustafa ATTAROGLU and Yalçın YILMAZ from BOZOGLU GROUP Construction Inc. for their collaboration.
İlk Sayfa Sayısı
[dc.identifier.startpage]
38
Son Sayfa Sayısı
[dc.identifier.endpage]
45
Dergi Adı
[dc.relation.journal]
Tunnelling and Underground Space Technology
Dergi Sayısı
[dc.identifier.issue]
1
Dergi Cilt Bilgisi
[dc.identifier.volume]
26
Tek Biçim Adres
[dc.identifier.uri]
https://dx.doi.org/10.1016/j.tust.2010.06.011
Tek Biçim Adres
[dc.identifier.uri]
https://hdl.handle.net/20.500.12628/7117
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Görüntülenme Sayısı ( Zaman Dağılımı )
Görüntülenme
8
09.12.2022 tarihinden bu yana
İndirme
1
09.12.2022 tarihinden bu yana
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18 Şubat 2024 08:22
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performance impact hammer prediction adaptive neuro-fuzzy inference system strength construction properties machine multiple regression excavators traditional laminated-foliated flysch constructed results models Although compared exhibits Impact better Elsevier selected excavation predicted according developed indicators statistical excavated
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