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Fuzzy and multiple regression modelling for evaluation of intact rock strength based on point load, schmidt hammer and sonic velocity

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dc.contributor.author Karakus, M.
dc.contributor.author Tutmez, B.
dc.date.accessioned 2022-10-06T11:27:08Z
dc.date.available 2022-10-06T11:27:08Z
dc.date.issued 2006
dc.identifier.issn 07232632 (ISSN)
dc.identifier.uri http://hdl.handle.net/11616/64697
dc.description.abstract Uniaxial Compressive Strength (UCS), considered to be one of the most useful rock properties for mining and civil engineering applications, has been estimated from some index test results by fuzzy and multiple regression modelling. Laboratory investigations including Uniaxial Compressive Strength (UCS), Point Load Index test (PL), Schmidt Hammer Hardness test (SHR) and Sonic velocity (Vp) test have been carried out on nine different rock types yielding to 305 tested specimens in total. Average values along with the standard deviations (Stdev) as well as Coefficients of variation (CoV) have been calculated for each rock type. Having constructed the Mamdani Fuzzy algorithm, UCS of intact rock samples was then predicted using a data driven fuzzy model. The predicted values derived from fuzzy model were compared with multi-linear statistical model. Comparison proved that the best model predictions have been achieved by fuzzy modelling in contrast to multi-linear statistical modelling. As a result, the developed fuzzy model based on point load, Schmidt hammer and sonic velocity can be used as a tool to predict UCS of intact rocks.
dc.source Rock Mechanics and Rock Engineering
dc.title Fuzzy and multiple regression modelling for evaluation of intact rock strength based on point load, schmidt hammer and sonic velocity


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