Record Details

Estimation of elastic constant of rocks using an ANFIS approach

DSpace at IIT Bombay

View Archive Info
 
 
Field Value
 
Title Estimation of elastic constant of rocks using an ANFIS approach
 
Creator SINGH, R
KAINTHOLA, A
SINGH, TN
 
Subject ANFIS
Fuzzy inference system
Density
Point load
Young's modulus
VAF
UNIAXIAL COMPRESSIVE STRENGTH
FUZZY MODEL
NEURO-FUZZY
IDENTIFICATION
PREDICTION
VELOCITY
MODULUS
SYSTEMS
 
Description The engineering properties of the rocks have the most vital role in planning of rock excavation and construction for optimum utilization of earth resources with greater safety and least damage to surroundings. The design and construction of structure is influenced by physico-mechanical properties of rock mass. Young's modulus provides insight about the magnitude and characteristic of the rock mass deformation due to change in stress field. The determination of the Young's modulus in laboratory is very time consuming and costly. Therefore, basic rock properties like point load, density and water absorption have been used to predict the Young's modulus. Point load, density and water absorption can be easily determined in field as well as laboratory and are pertinent properties to characterize a rock mass. The artificial neural network (ANN), fuzzy inference system (FIS) and neuro fuzzy are promising techniques which have proven to be very reliable in recent years. In, present study, neuro fuzzy system is applied to predict the rock Young's modulus to overcome the limitation of ANN and fuzzy logic. Total 85 dataset were used for training the network and 10 dataset for testing and validation of network rules. The network performance indices correlation coefficient, mean absolute percentage error (MAPE), root mean square error (RMSE), and variance account for (VAF) are found to be 0.6643, 7.583, 6.799, and 91.95 respectively, which endow with high performance of predictive neuro-fuzzy system to make use for prediction of complex rock parameter. (C) 2011 Elsevier B. V. All rights reserved.
 
Publisher ELSEVIER SCIENCE BV
 
Date 2014-10-15T08:02:52Z
2014-10-15T08:02:52Z
2012
 
Type Article
 
Identifier APPLIED SOFT COMPUTING, 12(1)40-45
http://dx.doi.org/10.1016/j.asoc.2011.09.010
http://dspace.library.iitb.ac.in/jspui/handle/100/14633
 
Language en