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Prediction of thermal conductivity of rock through physico-mechanical properties

DSpace at IIT Bombay

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Title Prediction of thermal conductivity of rock through physico-mechanical properties
 
Creator SINGH, TN
SINHA, S
SINGH, VK
 
Subject fuzzy model
sets
thermal conductivity
physico-mechanical properties of rock
artificial neural network
adaptive neuro fuzzy
p-wave velocity
fuzzy inference system
 
Description The transfer of energy between two adjacent parts of rock mainly depends on its thermal conductivity. Present study supports the use of artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) in the study of thermal conductivity along with other intrinsic properties of rock due to its increasing importance in many areas of rock engineering, agronomy and geo environmental engineering field. In recent years, considerable effort has been made to develop techniques to determine these properties. Comparative analysis is made to analyze the capabilities among six different models of ANN and ANFIS. ANN models are based on feedforward backpropagation network with training functions resilient backpropagation (RP), one step secant (OSS) and Powell-Beale restarts (CGB) and radial basis with training functions generalized regression neural network (GRNN) and more efficient design radial basis network (NEWRB). A data set of 136 has been used for training different models and 15 were used for testing purposes. A statistical analysis is made to show the consistency among them. ANFIS is proved to be the best among all the networks tried in this case with average absolute percentage error of 0.03% and regression coefficient of 1, whereas best performance shown by the FFBP (RP) with average absolute error of 2.26%. Thermal conductivity is predicted using P-wave velocity, porosity, bulk density, uniaxial compressive strength of rock as input parameters. (c) 2005
 
Publisher PERGAMON-ELSEVIER SCIENCE LTD
 
Date 2011-08-26T04:32:09Z
2011-12-26T12:57:16Z
2011-12-27T05:47:18Z
2011-08-26T04:32:09Z
2011-12-26T12:57:16Z
2011-12-27T05:47:18Z
2007
 
Type Article
 
Identifier BUILDING AND ENVIRONMENT, 42(1), 146-155
0360-1323
http://dx.doi.org/10.1016/j.buildenv.2005.08.022
http://dspace.library.iitb.ac.in/xmlui/handle/10054/11193
http://hdl.handle.net/10054/11193
 
Language en