Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy system

Deformation modulus is the important parameter in stability analysis of tunnels, dams and mining structures. In this paper, two predictive models including Mamdani fuzzy system (MFS) and multivariable regression analysis (MVRA) were developed to predict deformation modulus based on data obtained fro...

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Main Authors: Rezaei Mohammad, Asadizadeh Mostafa, Majdi Abbas, Hossaini Mohammad Farouq
Format: Article
Language:English
Published: Elsevier 2015-01-01
Series:International Journal of Mining Science and Technology
Online Access:http://www.sciencedirect.com/science/article/pii/S2095268614001761
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spelling doaj-43025dc745014814a9e821f81c6dc3db2020-11-25T02:30:52ZengElsevierInternational Journal of Mining Science and Technology2095-26862015-01-012512330Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy systemRezaei Mohammad0Asadizadeh Mostafa1Majdi Abbas2Hossaini Mohammad Farouq3Corresponding author. Tel.: +98 9188760448.; School of Mining Engineering, College of Engineering, University of Tehran, Tehran 1439957131, IranSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran 1439957131, IranSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran 1439957131, IranSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran 1439957131, IranDeformation modulus is the important parameter in stability analysis of tunnels, dams and mining structures. In this paper, two predictive models including Mamdani fuzzy system (MFS) and multivariable regression analysis (MVRA) were developed to predict deformation modulus based on data obtained from dilatometer tests carried out in Bakhtiary dam site and additional data collected from longwall coal mines. Models inputs were considered to be rock quality designation, overburden height, weathering, unconfined compressive strength, bedding inclination to core axis, joint roughness coefficient and fill thickness. To control the models performance, calculating indices such as root mean square error (RMSE), variance account for (VAF) and determination coefficient (R2) were used. The MFS results show the significant prediction accuracy along with high performance compared to MVRA results. Finally, the sensitivity analysis of MFS results shows that the most and the least effective parameters on deformation modulus are weathering and overburden height, respectively. Keywords: Deformation modulus, Dilatometer test, Mamdani fuzzy system, Multivariable regression analysishttp://www.sciencedirect.com/science/article/pii/S2095268614001761
collection DOAJ
language English
format Article
sources DOAJ
author Rezaei Mohammad
Asadizadeh Mostafa
Majdi Abbas
Hossaini Mohammad Farouq
spellingShingle Rezaei Mohammad
Asadizadeh Mostafa
Majdi Abbas
Hossaini Mohammad Farouq
Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy system
International Journal of Mining Science and Technology
author_facet Rezaei Mohammad
Asadizadeh Mostafa
Majdi Abbas
Hossaini Mohammad Farouq
author_sort Rezaei Mohammad
title Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy system
title_short Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy system
title_full Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy system
title_fullStr Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy system
title_full_unstemmed Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy system
title_sort prediction of representative deformation modulus of longwall panel roof rock strata using mamdani fuzzy system
publisher Elsevier
series International Journal of Mining Science and Technology
issn 2095-2686
publishDate 2015-01-01
description Deformation modulus is the important parameter in stability analysis of tunnels, dams and mining structures. In this paper, two predictive models including Mamdani fuzzy system (MFS) and multivariable regression analysis (MVRA) were developed to predict deformation modulus based on data obtained from dilatometer tests carried out in Bakhtiary dam site and additional data collected from longwall coal mines. Models inputs were considered to be rock quality designation, overburden height, weathering, unconfined compressive strength, bedding inclination to core axis, joint roughness coefficient and fill thickness. To control the models performance, calculating indices such as root mean square error (RMSE), variance account for (VAF) and determination coefficient (R2) were used. The MFS results show the significant prediction accuracy along with high performance compared to MVRA results. Finally, the sensitivity analysis of MFS results shows that the most and the least effective parameters on deformation modulus are weathering and overburden height, respectively. Keywords: Deformation modulus, Dilatometer test, Mamdani fuzzy system, Multivariable regression analysis
url http://www.sciencedirect.com/science/article/pii/S2095268614001761
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