Evaluation and prediction of bond strength of GFRP-bar reinforced concrete using artificial neural network optimized with genetic algorithm
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Zhibin Lin | F. Azarmi | Fei Yan | Xingyu Wang | K. Sobolev
[1] Zhili Gao,et al. Experimental study on bond durability of glass fiber reinforced polymer bars in concrete exposed to harsh environmental agents: Freeze-thaw cycles and alkaline-saline solution , 2017 .
[2] Zhibin Lin,et al. Bond durability assessment and long-term degradation prediction for GFRP bars to fiber-reinforced concrete under saline solutions , 2017 .
[3] Zhibin Lin,et al. Bond behavior of GFRP bar-concrete interface: Damage evolution assessment and FE simulation implementations , 2016 .
[4] Mijia Yang,et al. Bond mechanism and bond strength of GFRP bars to concrete: A review , 2016 .
[5] Fei Yan,et al. New strategy for anchorage reliability assessment of GFRP bars to concrete using hybrid artificial neural network with genetic algorithm , 2016 .
[6] Hyun-Do Yun,et al. Bond strength prediction for deformed steel rebar embedded in recycled coarse aggregate concrete , 2015 .
[7] Ravindra Nagar,et al. Modeling slump of ready mix concrete using genetic algorithms assisted training of Artificial Neural Networks , 2015, Expert Syst. Appl..
[8] Young Soo Yoon,et al. Local bond-slip response of GFRP rebar in ultra-high-performance fiber-reinforced concrete , 2015 .
[9] Antonio De Luca,et al. Reinforced Concrete with FRP Bars: Mechanics and Design , 2014 .
[10] Emadaldin Mohammadi Golafshani,et al. Artificial neural network and genetic programming for predicting the bond strength of GFRP bars in concrete , 2014, Materials and Structures.
[11] Rudolf Seracino,et al. Application of artificial neural networks to predict the bond strength of FRP-to-concrete joints , 2013 .
[12] J. Popp,et al. Sample size planning for classification models. , 2012, Analytica chimica acta.
[13] Rasoul Irani,et al. Evolving neural network using real coded genetic algorithm for permeability estimation of the reservoir , 2011, Expert Syst. Appl..
[14] Radhouane Masmoudi,et al. Thermal effects on GFRP rebars: experimental study and analytical analysis , 2010 .
[15] Arnaud Castel,et al. Artificial neural network model for steel–concrete bond prediction , 2009 .
[16] Ahmed M. Azmy,et al. Neural networks for predicting compressive strength of structural light weight concrete , 2009 .
[17] Joseph R. Rausch,et al. Sample size planning for statistical power and accuracy in parameter estimation. , 2008, Annual review of psychology.
[18] Mohammad Bagher Tavakoli,et al. Modified Levenberg-Marquardt Method for Neural Networks Training , 2007 .
[19] Yoke San Wong,et al. Effective training data selection in tool condition monitoring system , 2006 .
[20] R. Okelo,et al. Bond Strength of Fiber Reinforced Polymer Rebars in Normal Strength Concrete , 2005 .
[21] A. Nanni. Guide for the Design and Construction of Concrete Reinforced with FRP Bars (ACI 440.1R-03) , 2005 .
[22] Kypros Pilakoutas,et al. Bond Behavior of Fiber Reinforced Polymer Bars under Direct Pullout Conditions , 2004 .
[23] Rajkumar Thirumalainambi,et al. Training data requirement for a neural network to predict aerodynamic coefficients , 2003, SPIE Defense + Commercial Sensing.
[24] Russell V. Lenth,et al. Some Practical Guidelines for Effective Sample Size Determination , 2001 .
[25] C. Shield,et al. Bond of Glass Fiber Reinforced Plastic Reinforcing Bar for Consideration in Bridge Decks , 1999, SP-188: 4th Intl Symposium - Fiber Reinforced Polymer Reinforcement for Reinforced Concrete Structures.
[26] B. Benmokrane,et al. Investigation of bond in concrete member with fibre reinforced polymer (FRP) bars , 1998 .
[27] C. Adcock. Sample size determination : a review , 1997 .
[28] Gaetano Manfredi,et al. Behavior and Modeling of Bond of FRP Rebars to Concrete , 1997 .
[29] Brahim Benmokrane,et al. BOND STRENGTH AND LOAD DISTRIBUTION OF COMPOSITE GFRP REINFORCING BARS IN CONCRETE , 1996 .
[30] S. Tao,et al. Bond of GFRP Rebars to Ordinary-Strength Concrete , 1993, SP-138: Fiber-Reinforced-Plastic Reinforcement for Concrete Structures - International Symposium.
[31] Brahim Benmokrane,et al. Pullout and bond of glass-fibre rods embedded in concrete and cement grout , 1993 .
[32] Hiroshi Fukuyama,et al. Bond Performance of Concrete Members Reinforced With FRP Bars , 1991, SP-138: Fiber-Reinforced-Plastic Reinforcement for Concrete Structures - International Symposium.
[33] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[34] S. Stigler. Gauss and the Invention of Least Squares , 1981 .
[35] Mark Beale,et al. Neural Network Toolbox™ User's Guide , 2015 .
[36] Hadi Mazaheripour,et al. Experimental study on bond performance of GFRP bars in self-compacting steel fiber reinforced concrete , 2013 .
[37] Shahriar Quayyum. Bond behaviour of fibre reinforced polymer (FRP) rebars in concrete , 2010 .
[38] Yoshua Bengio,et al. Scaling learning algorithms towards AI , 2007 .
[39] Brahim Benmokrane,et al. Guide for the Design and Construction of Structural Concrete Reinforced with FRP Bars , 2006 .
[40] Masashi Sugiyama,et al. Training Data Selection for Optimal Generalization with Noise Variance Reduction in , 1998 .
[41] Zbigniew Michalewicz,et al. Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.
[42] Hota V. S. GangaRao,et al. BENDING AND BOND BEHAVIOR OF CONCRETE BEAMS REINFORCED WITH PLASTIC REBARS , 1991 .
[43] S. Daniali. Bond Strength of Fiber Reinforced Plastic Bars in Concrete , 1990 .