Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/xmlui/handle/10054/8580
Title: A comparative study of ANN and Neuro-fuzzy for the prediction of dynamic constant of rockmass
Authors: SINGH, TN
KANCHAN, R
VERMA, AK
SAIGAL, K
Keywords: P-Wave Velocity
Issue Date: 2005
Publisher: INDIAN ACADEMY SCIENCES
Citation: JOURNAL OF EARTH SYSTEM SCIENCE, 114(1), 75-86
Abstract: Physico-mechanical properties of rocks have great significance in all operational parts in mining activities, from exploration to final dispatch of material. Compressional wave velocity (p-wave velocity) and anisotropic behaviour of rocks are two such properties which help to understand the rock response under varying stress conditions. They also influence the breakage mechanism of rock. There are different methods to determine the p-wave velocity and anisotropy in situ and in the laboratory. These methods are cumbersome and time consuming. Fuzzy set theory, Fuzzy logic and Neural Networks techniques seem very well suited for typical geotechnical problems. In conjunction with statistics and conventional mathematical methods, hybrid methods can be developed that may prove to be a step forward in modeling geotechnical problems. Here, we have developed and compared two different models, Neuro-fuzzy systems (combination of fuzzy and artificial neural network systems) and Artificial neural network systems, for the prediction of compressional wave velocity.
URI: http://dx.doi.org/10.1007/BF02702010
http://dspace.library.iitb.ac.in/xmlui/handle/10054/8580
http://hdl.handle.net/10054/8580
ISSN: 0253-4126
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