| Non-destructive prediction of concrete compressive strength using neural networks A Khashman, P Akpinar Procedia Computer Science 108, 2358-2362, 2017 | 92 | 2017 |
| Intelligent classification system for concrete compressive strength P Akpinar, A Khashman Procedia Computer Science 120, 712-718, 2017 | 34 | 2017 |
| Intelligent prediction of concrete carbonation depth using neural networks P Akpinar, ID Uwanuakwa Bulletin of the Transilvania University of Brasov. Series III: Mathematics …, 2016 | 28 | 2016 |
| Investigation of the parameters influencing progress of concrete carbonation depth by using artificial neural networks P Akpinar, ID Uwanuakwa Materiales de Construcción 70 (337), e209-e209, 2020 | 24 | 2020 |
| Lunar soils, simulants and lunar construction materials: An overview YC Toklu, P Akpinar Advances in Space Research 70 (3), 762-779, 2022 | 23 | 2022 |
| Artificial intelligence prediction of rutting and fatigue parameters in modified asphalt binders ID Uwanuakwa, SIA Ali, MRM Hasan, P Akpinar, A Sani, KA Shariff Applied Sciences 10 (21), 7764, 2020 | 22 | 2020 |
| A combined study of expansive and tensile strength evolution of mortars under sulfate attack: implications on durability assessment P Akpinar, I Casanova Materiales de Construcción 60 (297), 59-68, 2010 | 12 | 2010 |
| Preliminary investigation of carbonation problem progress in concrete buildings of north Cyprus SI Malami, P Akpinar, MM Lawan MATEC Web of Conferences 203, 06007, 2018 | 9 | 2018 |
| A case study on the viability of using increased quantities of recycled concrete aggregates in structural concrete for extending environmental conservation in North Cyprus P Akpinar, H Al Attar Environmental Earth Sciences 80 (9), 367, 2021 | 8 | 2021 |
| Investigations on the influence of variations in hidden neurons and training data percentage on the efficiency of concrete carbonation depth prediction with ann ID Uwanuakwa, P Akpinar International Conference on Theory and Application of Soft Computing …, 2019 | 8 | 2019 |
| Machine learning in concrete's strength prediction SNA Al-Gburi, P Akpinar, A Helwan Computers and Concrete 29 (6), 433, 2022 | 6 | 2022 |
| Evaluation of carbonation depth evolution tendencies of reinforced concrete buildings located in coastal and inland areas of north cyprus QAH Houseen, P Akpınar IOP Conference Series: Materials Science and Engineering 800 (1), 012023, 2020 | 6 | 2020 |
| Lunar soil simulants-An assessment YC Toklu, P Akpınar 2019 9th International Conference on Recent Advances in Space Technologies …, 2019 | 5 | 2019 |
| A case study for exploring the alkali-aggregate reactivity of Cyprus aggregates A Zahedi, P Akpinar Case Studies in Construction Materials 16, e01000, 2022 | 4 | 2022 |
| Production of a set of lunar regolith simulants based on Apollo and Chinese samples YC Toklu, NÇ Açıkbaş, G Açıkbaş, AE Çerçevik, P Akpinar Advances in Space Research 72 (2), 565-576, 2023 | 3 | 2023 |
| The effect of silica fume inclusion on the properties of recycled concrete aggregate-containing concrete P Akpinar, HME Al Attar IOP Conference Series: Materials Science and Engineering 800 (1), 012001, 2020 | 3 | 2020 |
| Multi-approach studies on the mechanisms of sulfate-indeced degradation of cementitious materials P Akpinar Universitat Politècnica de Catalunya (UPC), 2007 | 3 | 2007 |
| Comparison of the Alkali-Silica Reactivity of North Cyprus and South Cyprus aggregates; preliminary studies using RILEM method P Akpinar, A Zahedi E3S Web of Conferences 304, 02001, 2021 | 2 | 2021 |
| Enhancing the reliability and accuracy of machine learning models for predicting carbonation progress in fly ash‐concrete: A multifaceted approach ID Uwanuakwa, P Akpınar Structural Concrete, 2024 | 1 | 2024 |
| A Non-destructive Method for the determination of Carbonation Time for Nominal Concrete Cover Depth Using Non-Linear En-semble Prediction SI Malami, P Akpinar E3S Web of Conferences 497, 02011, 2024 | | 2024 |
