Welcome to the InfoSci Platform
Reference Hub9
Prediction of The Uniaxial Compressive Strength of Rocks Materials

Prediction of The Uniaxial Compressive Strength of Rocks Materials

Nurcihan Ceryan, Nuray Korkmaz Can
Copyright: © 2018 |Pages: 66
ISBN13: 9781522527091|ISBN10: 1522527095|EISBN13: 9781522527107
DOI: 10.4018/978-1-5225-2709-1.ch002
Cite Chapter Cite Chapter

MLA

Ceryan, Nurcihan, and Nuray Korkmaz Can. "Prediction of The Uniaxial Compressive Strength of Rocks Materials." Handbook of Research on Trends and Digital Advances in Engineering Geology, edited by Nurcihan Ceryan, IGI Global, 2018, pp. 31-96. https://doi.org/10.4018/978-1-5225-2709-1.ch002

APA

Ceryan, N. & Can, N. K. (2018). Prediction of The Uniaxial Compressive Strength of Rocks Materials. In N. Ceryan (Ed.), Handbook of Research on Trends and Digital Advances in Engineering Geology (pp. 31-96). IGI Global. https://doi.org/10.4018/978-1-5225-2709-1.ch002

Chicago

Ceryan, Nurcihan, and Nuray Korkmaz Can. "Prediction of The Uniaxial Compressive Strength of Rocks Materials." In Handbook of Research on Trends and Digital Advances in Engineering Geology, edited by Nurcihan Ceryan, 31-96. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-2709-1.ch002

Export Reference

Mendeley
Favorite

Abstract

This study briefly will review determining UCS including direct and indirect methods including regression model soft computing techniques such as fuzzy interface system (FIS), artifical neural network (ANN) and least sqeares support vector machine (LS-SVM). These has advantages and disadvantages of these methods were discussed in term predicting UCS of rock material. In addition, the applicability and capability of non-linear regression, FIS, ANN and LS-SVM SVM models for predicting the UCS of the magnatic rocks from east Pondite, NE Turkey were examined. In these soft computing methods, porosity and P-durability secon index defined based on P-wave velocity and slake durability were used as input parameters. According to results of the study, the performanc of LS-SVM models is the best among these soft computing methods suggested in this study.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.