Development of a machine learning model for on-site evaluation of concrete compressive strength by SonReb

This publication has 36 references indexed in Scilit:

• I-SonReb: an improved NDT method to evaluate thein situstrength of carbonated concrete
  Nondestructive Testing and Evaluation, 2015
• Prediction of concrete compressive strength by combined non-destructive methods
  Meccanica, 2014
• Nondestructive evaluation of concrete strength: An historical review and a new perspective by combining NDT methods
  Construction and Building Materials, 2012
• Rebound surface hardness of concrete: Introduction of an empirical constitutive model
  Construction and Building Materials, 2011
• Estimating the Behavior of FRP-Strengthened RC Structural Members Using Artificial Neural Networks
  Procedia Engineering, 2011
• Neuro-fuzzy application for concrete strength prediction using combined non-destructive tests
  Magazine of Concrete Research, 2009
• Effect of carbonation on the rebound number and compressive strength of concrete
  Cement and Concrete Composites, 2009
• ANFIS: adaptive-network-based fuzzy inference system
  IEEE Transactions on Systems, Man, and Cybernetics, 1993
• Study on the introduction into Italy on the combined non-destructive method, for the determination ofin situ concrete strength
  Materials and Structures, 1979
• Analysis of answers to RILEM questionnaire on the schmidt rebound hammer
  Materials and Structures, 1969