| The effect of polypropylene fibers on asphalt performance S Tapkın Building and environment 43 (6), 1065-1071, 2008 | 338 | 2008 |
| Prediction of Marshall test results for polypropylene modified dense bituminous mixtures using neural networks S Tapkın, A Çevik, Ü Uşar Expert Systems with Applications 37 (6), 4660-4670, 2010 | 121 | 2010 |
| Repeated creep behavior of polypropylene fiber-reinforced bituminous mixtures S Tapkın, Ü Uşar, A Tuncan, M Tuncan Journal of Transportation Engineering 135 (4), 240-249, 2009 | 113 | 2009 |
| Accumulated strain prediction of polypropylene modified marshall specimens in repeated creep test using artificial neural networks S Tapkın, A Çevik, Ü Uşar Expert Systems with Applications 36 (8), 11186-11197, 2009 | 99 | 2009 |
| Mechanical evaluation of asphalt–aggregate mixtures prepared with fly ash as a filler replacement S Tapkın Canadian Journal of Civil Engineering 35 (1), 27-40, 2008 | 96 | 2008 |
| A mathematical model for predicting stripping potential of Hot Mix Asphalt HF Haghshenas, A Khodaii, M Khedmati, S Tapkin Construction and Building Materials 75, 488–495, 2015 | 68 | 2015 |
| A GIS-based multi-criteria model for offshore wind energy power plants site selection in both sides of the Aegean Sea E Tercan, S Tapkın, D Latinopoulos, MA Dereli, A Tsiropoulos, MF Ak Environmental Monitoring and Assessment 192 (652), 1-20, 2020 | 62 | 2020 |
| Rutting analysis of 100 mm diameter polypropylene modified asphalt specimens using gyratory and Marshall compactors S Tapkın, M Keskin Materials Research 16 (2), 546-564, 2013 | 42 | 2013 |
| A GIS‑based multi‑criteria evaluation for MSW landfill site selection in Antalya, Burdur, Isparta planning zone in Turkey E Tercan, MA Dereli, S Tapkın Environmental Earth Sciences 79 (246), 1-17, 2020 | 32 | 2020 |
| Optimal polypropylene fiber amount determination by using gyratory compaction, static creep and Marshall stability and flow analyses S Tapkın Construction and Building Materials 44, 399-410, 2013 | 31 | 2013 |
| Geographic information system-based investment system for photovoltaic power plants location analysis in Turkey E Tercan, BÖ Saracoglu, SS Bilgilioğlu, A Eymen, S Tapkın Environmental Monitoring and Assessment 192 (297), 1-26, 2020 | 30 | 2020 |
| Improved asphalt aggregate mix properties by portland cement modification S Tapkin M.Sc. thesis, Middle East Technical University, Civil Engineering Department …, 1998 | 30 | 1998 |
| Determination of the optimal polypropylene fiber addition to the dense bituminous mixtures by the aid of mechanical and optical means S Tapkin, Ş Özcan Baltic Journal of Road & Bridge Engineering 7 (1), 2012 | 20 | 2012 |
| Utilising neural networks and closed form solutions to determine static creep behaviour and optimal polypropylene amount in bituminous mixtures S Tapkın, A Çevik, Ş Özcan Materials Research 15 (6), 865-883, 2012 | 19 | 2012 |
| Estimation of polypropylene concentration of modified bitumen images by using k-NN and SVM classifiers S Tapkın, B Şengöz, G Şengül, A Topal, E Özçelik Journal of Computing in Civil Engineering, ASCE 29 (5), 04014055, 2013 | 17 | 2013 |
| Rutting prediction of asphalt mixtures modified by polypropylene fibers via repeated creep testing by utilising genetic programming S Tapkin, A Çevik, Ü Uşar, E Gülşan Materials Research 16 (2), 277-292, 2013 | 17 | 2013 |
| Polypropylene fiber-reinforced bitumen S Tapkin, Ü Uşar, Ş Özcan, A Çevik Polymer Modified Bitumen, 136-194, 2011 | 15 | 2011 |
| A recommended neural trip distribution model S TAPKIN MIDDLE EAST TECHNICAL UNIVERSITY, 2004 | 13 | 2004 |
| Modelling Marshall design test results of polypropylene modified asphalt by genetic programming techniques S Tapkın, A Çevik, U Ün, A Kurtoğlu Periodica Polytechnica Civil Engineering, 2015 | 12 | 2015 |
| Estimation Of Concrete Compressive Strength By Using Ultrasonic Pulse Velocities And Artificial Neural Networks S Tapkın, M Tuncan, Ö Arıöz, A Tuncan, K Ramyar Conference for Computer-Aided Engineering and System Modeling, 2006 | 11 | 2006 |
