Prediction of pressuremeter modulus and limit pressure of clayey soils by simple and non-linear multiple regression techniques: a case study from Mersin, Turkey

Limit Pressure ◽

Non Linear ◽

Regression Techniques ◽

Pressuremeter Modulus

Genetic programing and non-linear multiple regression techniques to predict backbreak in blasting operation

Engineering With Computers ◽

10.1007/s00366-015-0404-3 ◽

2015 ◽

Vol 32 (1) ◽

pp. 123-133 ◽

Cited By ~ 44

Author(s):

Roohollah Shirani Faradonbeh ◽

Masoud Monjezi ◽

Danial Jahed Armaghani

Keyword(s):

Multiple Regression ◽

Blasting Operation ◽

Non Linear ◽

Regression Techniques

Analysis of Regional Logistics Demand Prediction Based on Support Vector Non-Linear Multiple Regression

2009 International Conference on Management and Service Science ◽

10.1109/icmss.2009.5302556 ◽

2009 ◽

Cited By ~ 1

Author(s):

Zhi-Cheng Zheng ◽

Xin Liu

Keyword(s):

Multiple Regression ◽

Support Vector ◽

Regional Logistics ◽

Demand Prediction ◽

Non Linear ◽

Logistics Demand

Function development for appraising brittleness of intact rocks using genetic programming and non-linear multiple regression models

Engineering With Computers ◽

10.1007/s00366-016-0452-3 ◽

2016 ◽

Vol 33 (1) ◽

pp. 13-21 ◽

Cited By ~ 32

Author(s):

Manoj Khandelwal ◽

Roohollah Shirani Faradonbeh ◽

Masoud Monjezi ◽

Danial Jahed Armaghani ◽

Muhd Zaimi Bin Abd Majid ◽

...

Keyword(s):

Genetic Programming ◽

Multiple Regression ◽

Regression Models ◽

Multiple Regression Models ◽

Estimation of pressuremeter modulus and limit pressure of clayey soils by various artificial neural network models

Neural Computing and Applications ◽

10.1007/s00521-012-0900-y ◽

2012 ◽

Vol 23 (2) ◽

pp. 333-339 ◽

Cited By ~ 14

Author(s):

C. H. Aladag ◽

A. Kayabasi ◽

C. Gokceoglu

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Network Models ◽

Clayey Soils ◽

Neural Network Models ◽

Limit Pressure ◽

Artificial Neural ◽

Artificial Neural Network Models ◽

Pressuremeter Modulus

Estimation of meat amount by non-linear multiple regression equations using in vivo and carcass measurements on Teleorman Black Head lambs

Journal of Animal and Feed Sciences ◽

10.22358/jafs/67919/2016 ◽

2016 ◽

Vol 25 (4) ◽

pp. 292-301

Author(s):

C. Lazar ◽

M.Al. Gras ◽

R.S. Pelmus ◽

C.M. Rotar ◽

E. Ghita ◽

...

Keyword(s):

Multiple Regression ◽

Regression Equations ◽

Non Linear ◽

Black Head

Grapevine crop evapotranspiration and crop coefficient forecasting using linear and non-linear multiple regression models

Agricultural Water Management ◽

10.1016/j.agwat.2021.107317 ◽

2021 ◽

pp. 107317

Author(s):

Noa Ohana-Levi ◽

Alon Ben-Gal ◽

Sarel Munitz ◽

Yishai Netzer

Keyword(s):

Multiple Regression ◽

Regression Models ◽

Crop Coefficient ◽

Crop Evapotranspiration ◽

Multiple Regression Models ◽

Microfabrics-Based Approach to Predict Uniaxial Compressive Strength of Selected Amphibolites Schists Using Fuzzy Inference and Linear Multiple Regression Techniques

Environmental and Engineering Geoscience ◽

10.2113/gseegeosci.21.3.235 ◽

2015 ◽

Vol 21 (3) ◽

pp. 235-245

Author(s):

ESAMALDEEN ALI ◽

WU GUANG ◽

ABDELAZIM IBRAHIM

Keyword(s):

Compressive Strength ◽

Multiple Regression ◽

Uniaxial Compressive Strength ◽

Fuzzy Inference ◽

Regression Techniques

Expectation of Bead Shape using Non-linear Multiple Regression and Piecewise Cubic Hermite Interpolation in FCA Fillet Pipe Welding

Journal of Welding and Joining ◽

10.5781/kwjs.2009.27.5.042 ◽

2009 ◽

Vol 27 (5) ◽

pp. 42-48

Author(s):

Dae-Won Cho ◽

Suck-Joo Na ◽

Mok-Young Lee

Keyword(s):

Multiple Regression ◽

Hermite Interpolation ◽

Pipe Welding ◽

Pressuremeter Modulus and Limit Pressure of Clayey Soils Using GMDH-Type Neural Network and Genetic Algorithms

Geotechnical and Geological Engineering ◽

10.1007/s10706-017-0314-9 ◽

2017 ◽

Vol 36 (1) ◽

pp. 165-178 ◽

Cited By ~ 8

Author(s):

Reza Ziaie Moayed ◽

Afshin Kordnaeij ◽

Hossein Mola-Abasi

Keyword(s):

Neural Network ◽

Genetic Algorithms ◽

Clayey Soils ◽

Limit Pressure ◽

Pressuremeter Modulus

Characterization ofc-,L- andϕk-optimal designs for a class of non-linear multiple-regression models

Journal of the Royal Statistical Society Series B (Statistical Methodology) ◽

10.1111/rssb.12292 ◽

2018 ◽

Vol 81 (1) ◽

pp. 101-120 ◽

Cited By ~ 2

Author(s):

Dennis Schmidt

Keyword(s):

Multiple Regression ◽

Regression Models ◽

Optimal Designs ◽

Multiple Regression Models ◽