| Investigation of Performance Metrics in Regression Analysis and Machine Learning-based Prediction Models V Plevris, G Solorzano, NP Bakas, MEAB Seghier | 90* | |
| A collection of 30 multidimensional functions for global optimization benchmarking V Plevris, G Solorzano Data 7 (4), 46, 2022 | 29 | 2022 |
| Optimum design of RC footings with genetic algorithms according to ACI 318-19 G Solorzano, V Plevris Buildings 10 (6), 110, 2020 | 27 | 2020 |
| Pure random orthogonal search (PROS): a plain and elegant parameterless algorithm for global optimization V Plevris, NP Bakas, G Solorzano Applied Sciences 11 (11), 5053, 2021 | 22 | 2021 |
| Random forest-based algorithms for accurate evaluation of ultimate bending capacity of steel tubes MEAB Seghier, V Plevris, G Solorzano Structures 44, 261-273, 2022 | 17 | 2022 |
| Computational intelligence methods in simulation and modeling of structures: A state-of-the-art review using bibliometric maps G Solorzano, V Plevris Frontiers in Built Enviroment 8, 24, 2022 | 16 | 2022 |
| Literature Review of Historical Masonry Structures with Machine Learning V Plevris, G Solorzano, N Bakas | 9 | 2019 |
| ANN-based Surrogate Model for Predicting the Lateral Load Capacity of RC Shear Walls G Solorzano, V Plevris | 7* | |
| DNN-MLVEM: a data-driven macromodel for RC shear walls based on deep neural networks G Solorzano, V Plevris Mathematics 11 (10), 2347, 2023 | 6 | 2023 |
| Design of Reinforced Concrete Isolated Footings under Axial Loading with Artificial Neural networks G Solorzano, V Plevris 14th ECCOMAS Thematic Conference on Evolutionary and Deterministic Methods …, 2021 | 6 | 2021 |
| An Open‐Source Framework for Modeling RC Shear Walls Using Deep Neural Networks G Solorzano, V Plevris Advances in Civil Engineering 2023 (1), 7953869, 2023 | 4 | 2023 |
| Prediction of the Eigenperiods of MDOF Shear Buildings Using Neural Networks V Plevris, G Solorzano Proceedings of the 8th International Conference on Computational Methods in …, 2021 | 4 | 2021 |
| A Collection of 30 Multidimensional Functions for Global Optimization Benchmarking. Data 2022, 7, 46 V Plevris, G Solorzano s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2022 | 1 | 2022 |
| Using artificial intelligence techniques for the accurate estimation of the ultimate pure bending of steel circular tubes MEA Ben Seghier, V Plevris, G Solorzano 8th European Congress on Computational Methods in Applied Sciences and …, 2022 | | 2022 |
Vagelis PlevrisQatar University在 qu.edu.qa 的电子邮件经过验证
Vagelis PlevrisQatar University在 qu.edu.qa 的电子邮件经过验证
Nikolaos BakasGRNET在 grnet.gr 的电子邮件经过验证