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Title

Multivariate Estimation of Rock Mass Characteristics Respect to Depth Using ANFIS Based Subtractive Clustering- Khorramabad - Polezal Freeway Tunnels

Year: 1395
COI: JR_JEG-10-4_002
Language: EnglishView: 132
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Authors

S.H. Moosavi - Engineer of Geo-Techniques and Excavation Devision, Imensazan Engineering Consulting Co, Water Conveyor Tunnel of Nosud Project,
M. Sharifzadeh - Faculty of Mining Eng, Mining and Metallurgy, Amirkabir University of Technology

Abstract:

Combination of Adoptive Network based Fuzzy Inference System (ANFIS) and subtractive clustering (SC) has been used for estimation of deformation modulus (Em) and rock mass strength (UCSm) considering depth of measurement. To do this, learning of the ANFIS based subtractive clustering (ANFISBSC) was performed firstly on 125 measurements of 9 variables such as rock mass strength (UCSm), deformation modulus (Em), depth, spacing, persistence, aperture, intact rock strength (UCSi), geomechanical rating (RMR) and elastic modulus (Ei). Then, at second phase, testing the trained ANFISBSC structure has been perfomed on 40 data measurements. Therefore, predictive rock mass models have been developed for 2-6 variables where model complexity influences the estimation accuracy. Results of multivariate simulation of rock mass for estimating UCSm and Em have shown that accuracy of the ANFISBSC method increases coincident with development of model from 2 variables to 6 variables. According to the results, 3-variable model of ANFISBSC method has general estimation of both UCSm and Em corresponding with 20% to 30% error while the results of multivariate analysis are successfully improved by 6-variable model with error of less than 3%. Also, dip of the fitted line on data point of measured and estimated UCSm and Em for 6-variable model approaches about 1 respect to 0.94 for 3- variable model. Therefore, it can be concluded that 6-variable model of ANFISBSC gives reasonable prediction of UCSm and Em.

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Paper COI Code

This Paper COI Code is JR_JEG-10-4_002. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/791423/

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If you want to refer to this Paper in your research work, you can simply use the following phrase in the resources section:
Moosavi, S.H. and Sharifzadeh, M.,1395,Multivariate Estimation of Rock Mass Characteristics Respect to Depth Using ANFIS Based Subtractive Clustering- Khorramabad - Polezal Freeway Tunnels,https://civilica.com/doc/791423

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