Predicting the compressive strength of ground granulated blast furnace slag concrete using artificial neural network C Bilim, CD Atiş, H Tanyildizi, O Karahan Advances in Engineering Software 40 (5), 334-340, 2009 | 383 | 2009 |
Comparison of artificial neural network and fuzzy logic models for prediction of long-term compressive strength of silica fume concrete F Özcan, CD Atiş, O Karahan, E Uncuoğlu, H Tanyildizi Advances in Engineering Software 40 (9), 856-863, 2009 | 325 | 2009 |
The effect of high temperature on compressive strength and splitting tensile strength of structural lightweight concrete containing fly ash H Tanyildizi, A Coskun Construction and building materials 22 (11), 2269-2275, 2008 | 266 | 2008 |
Estimation of compressive strength of self compacting concrete containing polypropylene fiber and mineral additives exposed to high temperature using artificial neural network M Uysal, H Tanyildizi Construction and Building Materials 27 (1), 404-414, 2012 | 230 | 2012 |
Performance of lightweight concrete with silica fume after high temperature H Tanyildizi, A Coskun Construction and Building Materials 22 (10), 2124-2129, 2008 | 164 | 2008 |
Statistical analysis for mechanical properties of polypropylene fiber reinforced lightweight concrete containing silica fume exposed to high temperature H Tanyildizi Materials & Design 30 (8), 3252-3258, 2009 | 119 | 2009 |
Mechanical properties of geopolymer concrete containing polyvinyl alcohol fiber exposed to high temperature H Tanyildizi, Y Yonar Construction and Building Materials 126, 381-387, 2016 | 112 | 2016 |
Predicting the core compressive strength of self-compacting concrete (SCC) mixtures with mineral additives using artificial neural network M Uysal, H Tanyildizi Construction and Building Materials 25 (11), 4105-4111, 2011 | 112 | 2011 |
Application of Taguchi method for optimization of concrete strengthened with polymer after high temperature H Tanyildizi, M Şahin Construction and Building materials 79, 97-103, 2015 | 91 | 2015 |
Effect of temperature, carbon fibers, and silica fume on the mechanical properties of lightweight concretes H Tanyildizi New carbon materials 23 (4), 339-344, 2008 | 87 | 2008 |
Modeling mechanical performance of lightweight concrete containing silica fume exposed to high temperature using genetic programming H Tanyildizi, A Çevik Construction and Building Materials 24 (12), 2612-2618, 2010 | 76 | 2010 |
Fuzzy logic model for the prediction of bond strength of high-strength lightweight concrete H Tanyildizi Advances in Engineering Software 40 (3), 161-169, 2009 | 69 | 2009 |
Fuzzy logic model for prediction of mechanical properties of lightweight concrete exposed to high temperature H Tanyildizi Materials & Design 30 (6), 2205-2210, 2009 | 67 | 2009 |
Prediction of the strength properties of carbon fiber‐reinforced lightweight concrete exposed to the high temperature using artificial neural network and support vector machine H Tanyildizi Advances in civil engineering 2018 (1), 5140610, 2018 | 62 | 2018 |
Comparison of extreme learning machine and deep learning model in the estimation of the fresh properties of hybrid fiber-reinforced SCC C Kina, K Turk, E Atalay, I Donmez, H Tanyildizi Neural Computing and Applications 33, 11641-11659, 2021 | 52 | 2021 |
Variance analysis of crack characteristics of structural lightweight concrete containing silica fume exposed to high temperature H Tanyildizi Construction and Building Materials 47, 1154-1159, 2013 | 49 | 2013 |
An artificial neural network approach for prediction of long-term strength properties of steel fiber reinforced concrete containing fly ash O Karahan, H Tanyildizi, CD Atis Journal of Zhejiang University-SCIENCE A 9, 1514-1523, 2008 | 45 | 2008 |
Predicting the geopolymerization process of fly ash-based geopolymer using deep long short-term memory and machine learning H Tanyildizi Cement and Concrete Composites 123, 104177, 2021 | 42 | 2021 |
Determination of the principal parameter of ultrasonic pulse velocity and compressive strength of lightweight concrete by using variance method AC H. TANYILDIZI Russian Journal of Nondestructive Testing 44 (9), 639-646, 2008 | 36 | 2008 |
Deep learning model for estimating the mechanical properties of concrete containing silica fume exposed to high temperatures H Tanyildizi, A Şengür, Y Akbulut, M Şahin Frontiers of Structural and Civil Engineering 14, 1316-1330, 2020 | 35 | 2020 |