Applying several machine learning approaches for prediction of unconfined compressive strength of stabilized pond ashes

Estimating Compressive Strength of High Performance Concrete with Gaussian Process Regression Model

(2016) Nhat-Duc Hoang et al.   Advances in Civil Engineering

Prediction of unconfined compressive strength of carbonate rocks using artificial neural networks

(2012) Nurcihan Ceryan et al.   Environmental Earth Sciences

Engineering Properties of Copper Slag–Fly Ash–Dolime Mix and Its Utilization in the Base Course of Flexible Pavements

(2012) J. T. Shahu et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Prediction of unconfined compressive strength of rock surrounding a roadway using artificial neural network

(2012) Abbas Majdi et al.   NEURAL COMPUTING & APPLICATIONS

Modelling pile capacity using Gaussian process regression

(2010) Mahesh Pal et al.   COMPUTERS AND GEOTECHNICS

Predictive models for forecasting hourly urban water demand

(2010) Manuel Herrera et al.   JOURNAL OF HYDROLOGY

M5 model tree based modelling of reference evapotranspiration

(2009) Mahesh Pal et al.   HYDROLOGICAL PROCESSES

Prediction of blast-induced ground vibration using artificial neural network

(2009) Manoj Khandelwal et al.   INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES

Application of Random Forest Approach to QSAR Prediction of Aquatic Toxicity

(2009) Pavel G. Polishchuk et al.   Journal of Chemical Information and Modeling

Support vector machine applied to settlement of shallow foundations on cohesionless soils

(2007) Pijush Samui   COMPUTERS AND GEOTECHNICS

Slope reliability analysis using a support vector machine

(2007) Hong-bo Zhao   COMPUTERS AND GEOTECHNICS