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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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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