Prediction model for compressive strength of basic concrete mixture using artificial neural networks

Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network

(2012) Masoud Monjezi et al.   NEURAL COMPUTING & APPLICATIONS

A comparative study of generalized regression neural network approach and adaptive neuro-fuzzy inference systems for prediction of unconfined compressive strength of rocks

(2012) Rajesh Singh et al.   NEURAL COMPUTING & APPLICATIONS

Soft computing method for assessment of compressional wave velocity

(2012) R. Singh et al.   Scientia Iranica

Prediction of the effect of varying cure conditions and w/c ratio on the compressive strength of concrete using artificial neural networks

(2011) Hasbi Yaprak et al.   NEURAL COMPUTING & APPLICATIONS

Estimation of strength parameters of rock using artificial neural networks

(2010) Kripamoy Sarkar et al.   Bulletin of Engineering Geology and the Environment

Predicting the compressive strength of mortars containing metakaolin by artificial neural networks and fuzzy logic

(2009) Mustafa Sarıdemir   ADVANCES IN ENGINEERING SOFTWARE

Prediction of the compressive strength of no-slump concrete: A comparative study of regression, neural network and ANFIS models

(2009) Jafar Sobhani et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction of macerals contents of Indian coals from proximate and ultimate analyses using artificial neural networks

(2009) Manoj Khandelwal et al.   FUEL

Prediction of blast-induced ground vibration using artificial neural network

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

Prediction of compressive strength of heavyweight concrete by ANN and FL models

(2009) C. Başyigit et al.   NEURAL COMPUTING & APPLICATIONS

Contribution to the Concrete Strength versus Water-Cement Ratio Relationship

(2008) Sandor Popovics et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Prediction of compressive strength of concrete containing fly ash using artificial neural networks and fuzzy logic

(2007) İlker Bekir Topçu et al.   COMPUTATIONAL MATERIALS SCIENCE