| An artificial neural network model for predicting compression strength of heat treated woods and comparison with a multiple linear regression model S Tiryaki, A Aydın Construction and Building Materials 62, 102-108, 2014 | 177 | 2014 |
| Predicting modulus of rupture (MOR) and modulus of elasticity (MOE) of heat treated woods by artificial neural networks S Tiryaki, C Hamzaçebi Measurement 49, 266-274, 2014 | 93 | 2014 |
| Using artificial neural networks for modeling surface roughness of wood in machining process S Tiryaki, A Malkoçoğlu, Ş Özşahin Construction and Building Materials 66, 329-335, 2014 | 75 | 2014 |
| Üniversite öğrencilerinin kaygı düzeylerini etkileyen faktörleri belirlemeye yönelik bir çalışma (KTÜ örneği) A Aydın, S Tiryaki Kastamonu üniversitesi orman fakültesi dergisi 17 (4), 715-722, 2017 | 63* | 2017 |
| Comparison of artificial neural network and multiple linear regression models to predict optimum bonding strength of heat treated woods S Tiryaki, Ş Özşahin, İ Yıldırım International Journal of Adhesion and Adhesives 55, 29-36, 2014 | 55 | 2014 |
| Impact of performance appraisal on employee motivation and productivity in Turkish forest products industry: A structural equation modeling analysis A Aydın, S Tiryaki Drvna industrija 69 (2), 101-111, 2018 | 54 | 2018 |
| Investigation and neural network prediction of wood bonding quality based on pressing conditions S Bardak, S Tiryaki, G Nemli, A Aydın International Journal of Adhesion and Adhesives 68, 115-123, 2016 | 40 | 2016 |
| Employing artificial neural networks for minimizing surface roughness and power consumption in abrasive machining of wood S Tiryaki, Ş Özşahin, A Aydın European Journal of Wood and Wood Products 75, 347-358, 2017 | 39 | 2017 |
| Experimental investigation and prediction of bonding strength of Oriental beech (Fagus orientalis Lipsky) bonded with polyvinyl acetate adhesive S Tiryaki, S Bardak, T Bardak Journal of Adhesion Science and Technology 29 (23), 2521-2536, 2015 | 37 | 2015 |
| Predictive performance of artificial neural network and multiple linear regression models in predicting adhesive bonding strength of wood S Bardak, S Tiryaki, T Bardak, A Aydin Strength of Materials 48, 811-824, 2016 | 27 | 2016 |
| Analysis of volumetric swelling and shrinkage of heat treated woods: Experimental and artificial neural network modeling approach S Tiryaki, S Bardak, A Aydin, G Nemli Maderas. Ciencia y tecnología 18 (3), 477-492, 2016 | 25 | 2016 |
| Evaluation of process parameters for lower surface roughness in wood machining by using Taguchi design methodology S Tiryaki, C Hamzaçebi, A Malkoçoğlu European Journal of Wood and Wood Products 73, 537-545, 2015 | 22 | 2015 |
| The influence of raw material growth region, anatomical structure and chemical composition of wood on the quality properties of particleboards S Bardak, G Nemli, S Tiryaki Maderas. Ciencia y tecnología 19 (3), 363-372, 2017 | 21 | 2017 |
| YENİ HİTİT SANATI ÜZERİNE İKONOGRAFİK ARAŞTIRMALAR 1: ÜZÜM SALKIMI VE/VEYA BAŞAK FİLİZİ TAŞIYANLAR SG TİRYAKİ Cedrus 1, 33-53, 2013 | 20 | 2013 |
| An application of artificial neural networks for modeling formaldehyde emission based on process parameters in particleboard manufacturing process İ Akyüz, Ş Özşahin, S Tiryaki, A Aydın Clean Technologies and Environmental Policy 19, 1449-1458, 2017 | 17 | 2017 |
| Performance evaluation of multiple adaptive regression splines, teaching–learning based optimization and conventional regression techniques in predicting mechanical properties … S Tiryaki, H Tan, S Bardak, M Kankal, S Nacar, H Peker European journal of wood and wood products 77, 645-659, 2019 | 15 | 2019 |
| Artificial neural network modelling to predict optimum power consumption in wood machining S Tiryaki, A Malkocoglu, S Ozsahin Drewno. Prace Naukowe. Doniesienia. Komunikaty 59 (196), 2016 | 15 | 2016 |
| Modeling of wood bonding strength based on soaking temperature and soaking time by means of artificial neural networks S Tiryaki, S Bardak, A AYDIN International Journal of Intelligent Systems and Applications in Engineering …, 2016 | 13 | 2016 |
| Application of artificial neural networks for predicting tensile index and brightness in bleaching pulp OT Okan, I Deniz, S Tiryaki Maderas. Ciencia y tecnología 17 (3), 571-584, 2015 | 12 | 2015 |
| Utilization potential of waste wood subjected to insect and fungi degradation for particleboard manufacturing G Nemli, E Ayan, N Ay, S Tiryaki European journal of wood and wood products 76, 759-766, 2018 | 11 | 2018 |
