Intergration of neural networks with NDE for concrete strength prediction

H.J.Kim, L. Chung, T.W. Park (2010). "Intergration of neural networks with NDE for concrete strength prediction." In Proceedings of FraMCoS 7, Jeju, South Korea.

H.J.Kim, L. Chung, T.W. Park. "Intergration of neural networks with NDE for concrete strength prediction." Paper presented at FraMCoS 7, Jeju, South Korea, 2010.

H.J.Kim, L. Chung, T.W. Park, "Intergration of neural networks with NDE for concrete strength prediction," in Proc. FraMCoS 7, Jeju, South Korea, 2010.

@inproceedings{h-j-kim2010,
  title     = {Intergration of neural networks with NDE for concrete strength prediction},
  author    = {H.J.Kim, L. Chung, T.W. Park},
  year      = {2010},
  booktitle = {Proceedings of FraMCoS 7},
  address   = {Jeju, South Korea},
}

TY  - CPAPER
TI  - Intergration of neural networks with NDE for concrete strength prediction
AU  - H.J.Kim
AU  - L. Chung
AU  - T.W. Park
PY  - 2010
T2  - Proceedings of FraMCoS 7
CY  - Jeju, South Korea
UR  - https://framcos.org/wp-content/uploads/framcos-papers/Intergration_of_neural_networks_with_NDE_for_concrete_strength_prediction.pdf
AB  - The application of neuro-fuzzy inference system to predict the compressive strengths of con- crete is presented in this study. To investigate the influence of various parameters which affect the compres- sive strength, 2000 data samples were used for the analysis. Adaptive neuro-fuzzy inference system (ANFIS) was introduced for training and testing the data obtained from technical literatures. To reflect the effects of other uncertain parameters and in situ conditions, the results of non-destructive tests (NDT) such as ultrasonic pulse velocity (UPV) test and rebound hammer test were included as input parameters, in addition to mix pro- portion and curing histories.…
ER  -