Machine learning for durability and service-life assessment of reinforced concrete structures: Recent advances and future directions WZ Taffese, E Sistonen Automation in Construction 77, 1-14, 2017 | 197 | 2017 |
CaPrM: Carbonation prediction model for reinforced concrete using machine learning methods WZ Taffese, E Sistonen, J Puttonen Construction and Building Materials 100, 70–82, 2015 | 103 | 2015 |
Embodied Energy and CO2 Emissions of Widely Used Building Materials: The Ethiopian Context WZ Taffese, KA Abegaz Buildings 9 (6), 136, 2019 | 61 | 2019 |
Suitability investigation of recycled concrete aggregates for concrete production: An experimental case study WZ Taffese Advances in Civil Engineering 2018 (Article ID 8368351), 11pages, 2018 | 50 | 2018 |
Service Life Prediction of Repaired Structures Using Concrete Recasting Method: State-of-the-Art WZ Taffese, E Sistonen Procedia Engineering 57, 1138-1144, 2013 | 50 | 2013 |
Case-based reasoning and neural networks for real estate valuation. WZ Taffese Artificial Intelligence and Applications, 98-104, 2007 | 48 | 2007 |
Internet of Things based Durability Monitoring and Assessment of Reinforced Concrete Structures WZ Taffese, E Nigussie, J Isoaho Procedia Computer Science 155, 672-679, 2019 | 41 | 2019 |
Neural network based hygrothermal prediction for deterioration risk analysis of surface-protected concrete façade element WZ Taffese, E Sistonen Construction and building materials 113, 34-48, 2016 | 34 | 2016 |
A machine learning method for predicting the chloride migration coefficient of concrete WZ Taffese, L Espinosa-Leal Construction and Building Materials 348, 128566, 2022 | 33 | 2022 |
Prediction of chloride resistance level of concrete using machine learning for durability and service life assessment of building structures WZ Taffese, L Espinosa-Leal Journal of Building Engineering 60, 105146, 2022 | 31 | 2022 |
Rice husk ash in concrete SA Endale, WZ Taffese, DH Vo, MD Yehualaw Sustainability 15 (1), 137, 2022 | 27 | 2022 |
Significance of chloride penetration controlling parameters in concrete: Ensemble methods WZ Taffese, E Sistonen Construction and Building Materials 139, 9-23, 2017 | 26 | 2017 |
Prediction of compaction and strength properties of amended soil using machine learning WZ Taffese, KA Abegaz Buildings 12 (5), 613, 2022 | 25 | 2022 |
Prediction of Concrete Carbonation Depth using Decision Trees WZ Taffese, E Sistonen, J Puttonen European Symposium on Artificial Neural Networks, Computational …, 2015 | 24 | 2015 |
A Survey on Application of Artificial Intelligence in Real Estate Industry WZ Taffese 3rd International Conference on Artificial Intelligence in Engineering …, 2006 | 22 | 2006 |
Low-cost eco-friendly building material: a case study in Ethiopia WZ Taffese International Journal of Civil, Environmental, Structural, Construction and …, 2012 | 19 | 2012 |
Optimized neural network based carbonation prediction model WZ Taffese, F Al-Neshawy, E Sistonen, M Ferreira International Symposium Non-Destructive Testing in Civil Engineering (NDT-CE …, 2015 | 18 | 2015 |
Artificial intelligence for prediction of physical and mechanical properties of stabilized soil for affordable housing WZ Taffese, KA Abegaz Applied Sciences 11 (16), 7503, 2021 | 17 | 2021 |
Autonomous corrosion assessment of reinforced concrete structures: Feasibility study WZ Taffese, E Nigussie Sensors 20 (23), 6825, 2020 | 14 | 2020 |
Data-driven method for enhanced corrosion assessment of reinforced concrete structures WZ Taffese University of Turku, 2020 | 9 | 2020 |