An artificial intelligence approach for concrete hardened property estimation
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[1] Tu T. Nguyen,et al. Modeling of CLT creep behavior and real-time hybrid simulation of a CLT-LiFS building , 2017 .
[2] Tung Pham Thanh,et al. Compressive Strength Evaluation of Fiber-Reinforced High-Strength Self-Compacting Concrete with Artificial Intelligence , 2020 .
[3] C. Poon,et al. Prediction of compressive strength of recycled aggregate concrete using artificial neural networks , 2013 .
[4] M. A. Bhatti,et al. Predicting the compressive strength and slump of high strength concrete using neural network , 2006 .
[5] Tarek Zayed,et al. GPR-Based Fuzzy Model for Bridge Deck Corrosiveness Index , 2016 .
[6] Vinay Agrawal,et al. Prediction of Slump in Concrete using Artificial Neural Networks , 2010 .
[7] Rafat Siddique,et al. Prediction of compressive strength of self-compacting concrete containing bottom ash using artificial neural networks , 2011, Adv. Eng. Softw..
[8] B. V. Venkatarama Reddy,et al. Prediction of compressive strength of SCC and HPC with high volume fly ash using ANN , 2009 .
[9] H. Ang,et al. ANFIS based Modelling of dewatering performance and polymer dose optimization in a wastewater treatment plant , 2018 .
[10] Harun Tanyildizi,et al. Estimation of compressive strength of self compacting concrete containing polypropylene fiber and mineral additives exposed to high temperature using artificial neural network , 2012 .
[11] John W. van de Lindt,et al. Seismic assessment of a three-story wood building with an integrated CLT-lightframe system using RTHS , 2018, Engineering Structures.
[12] Thang N. Dao,et al. Numerical Model for Creep Behavior of Axially Loaded CLT Panels , 2019, Journal of Structural Engineering.
[13] Dinh Van Thuat,et al. A deep learning-based procedure for estimation of ultimate load carrying of steel trusses using advanced analysis , 2019, Journal of Science and Technology in Civil Engineering (STCE) - NUCE.
[14] Kien Dinh,et al. Prediction of bridge deck condition rating based on artificial neural networks , 2019, Journal of Science and Technology in Civil Engineering (STCE) - NUCE.
[15] Ahmed M. Azmy,et al. Neural networks for predicting compressive strength of structural light weight concrete , 2009 .
[16] Mehdi Nikoo,et al. Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive strength of concrete , 2017, Frontiers of Structural and Civil Engineering.
[17] Harun Tanyildizi,et al. Predicting the core compressive strength of self-compacting concrete (SCC) mixtures with mineral additives using artificial neural network , 2011 .
[18] Yang Yu,et al. A novel optimised self-learning method for compressive strength prediction of high performance concrete , 2018, Construction and Building Materials.
[19] Amit Kumar Gorai,et al. Development of ANFIS models for air quality forecasting and input optimization for reducing the computational cost and time , 2016 .
[20] Ahmet Tortum,et al. Neural networks analysis of compressive strength of lightweight concrete after high temperatures , 2013 .
[21] Robert A. Caughey,et al. Reinforced concrete-mechanics and design , 1933 .
[22] J. Sobhani,et al. Prediction of the compressive strength of no-slump concrete: A comparative study of regression, neural network and ANFIS models , 2010 .