Prediction of the strength and elasticity modulus of gypsum using multiple regression, ANN, and ANFIS models

By Isik Yilmaz, Gürkan Yuksek. 2009

307 citations recorded by the source corpus.

Subfields: Building and Construction, Environmental Engineering, Soil Science

View Paper: https://www.semanticscholar.org/paper/b9f2bfc30f905c9dcc99c63c5a04932d3d01baf0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. J. Bolouri Bazaz
2. Parisa Rahimzadeh Oskooei
3. Behnam Ghorbani
4. Ehsan Sadrossadat
5. Sefer Beran Çelik

In Environmental Engineering

1. J. Bolouri Bazaz
2. Parisa Rahimzadeh Oskooei
3. Behnam Ghorbani
4. Ehsan Sadrossadat
5. Sefer Beran Çelik

In Soil Science

1. J. Bolouri Bazaz
2. Parisa Rahimzadeh Oskooei
3. Behnam Ghorbani
4. Ehsan Sadrossadat
5. Sefer Beran Çelik

Citations in the corpus

• Numerical ANFIS-Based Formulation for Prediction of the Ultimate Axial Load Bearing Capacity of Piles Through CPT Data (2018, methodology): “It is one of the most frequently used methods in fuzzy applications (Lee 1990; Mishra et al. 2015; Sadrossadat et al. 2016b; Yilmaz and Yuksek 2009).”
• Prediction of uniaxial compressive strength of carbonate rocks from nondestructive tests using multivariate regression and LS-SVM methods (2019, methodology): “…Sönmez et al. 2004; Kahraman and Alber 2006; Sönmez et al. 2006; Tütmez and Tercan 2007; Baykasoğlu et al. 2008; Tiryaki 2008; Yılmaz and Yüksek 2008; Yılmaz and Yüksek 2009; Sarkar et al. 2010; Yağız et al. 2012; Ceryan et al. 2012; Ceryan et al. 2013a; Mishra and Basu 2013; Mishra et al. 2015).”