The influence of input data standardization method on prediction accuracy of artificial neural networks H Anysz, A Zbiciak, N Ibadov Procedia Engineering 153, 66-70, 2016 | 94 | 2016 |
Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks H Anysz, P Narloch Materials 12 (9), 2019 | 57 | 2019 |
Feature Importance of Stabilised Rammed Earth Components Affecting the Compressive Strength Calculated with Explainable Artificial Intelligence Tools H Anysz, Ł Brzozowski, W Kretowicz, P Narloch Materials 13 (11), 1-20, 2020 | 50 | 2020 |
Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests A Beskopylny, A Lyapin, H Anysz, B Meskhi, A Veremeenko, A Mozgovoy Materials 13 (11), 2020 | 46 | 2020 |
The association analysis for risk evaluation of significant delay occurrence in the completion date of construction project H Anysz, B Buczkowski International Journal of Environmental Science and Technology, 2019 | 45 | 2019 |
Pareto Optimal Decisions in Multi-Criteria Decision Making Explained with Construction Cost Cases H Anysz, A Nicał, Ž Stević, M Grzegorzewski, K Sikora Symmetry 13, 2021 | 43 | 2021 |
Predicting Compressive Strength of Cement-Stabilized Rammed Earth Based on SEM Images Using Computer Vision and Deep Learning P Narloch, A Hassanat, AS Tarawneh, H Anysz, J Kotowski, ... Applied Sciences 9 (23), 1-14, 2019 | 43 | 2019 |
The comparison of ANN classifier to the neuro-fuzzy system for a collusion detection in the tender procedures in the road construction sector H Anysz, A Foremny, J Kulejewski IOP Conference Series: Materials Science and Engineering 471, 2019 | 27 | 2019 |
Przyczyny powstawania opóźnień w realizacji kontraktów budowlanych: analiza wstępnych wyników badania ankietowego H Anysz, A Zbiciak Autobusy: technika, eksploatacja, systemy transportowe 14 (3), 963-972, 2013 | 27 | 2013 |
The quality management in precast concrete production and delivery processes supported by association analysis A Nicał, H Anysz International Journal of Environmental Science and Technology, 577–590, 2020 | 25 | 2020 |
Neuro-fuzzy predictions of construction site completion dates H Anysz, N Ibadov Technical Transactions 114 (6), 51-58, 2017 | 17 | 2017 |
Delineating Groundwater Recharge Potential through Remote Sensing and Geographical Information Systems A Maqsoom, B Aslam, N Khalid, F Ullah, H Anysz, AH Almaliki, ... Water 14 (1824), 2022 | 16 | 2022 |
Wykorzystanie sztucznych sieci neuronowych do oceny możliwości wystąpienia opóźnień w realizacji kontraktów budowlanych H Anysz Warsaw University of Technology, Department of Civil Engineering, 2017 | 15 | 2017 |
Estimating potential losses of the client in public procurement in case of collusion utilizing a MLP neural networks H Anysz, A Foremny, J Kulejewski Technical Transactions. Civil Engineering, 105-118, 2014 | 15 | 2014 |
The profit as in-company evaluation of the construction site effectiveness H Anysz MATEC Web of Conferences 117, 00009, 2017 | 14 | 2017 |
Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools H Anysz, M Apollo, B Grzyl Symmetry 13 (5), 2021 | 13* | 2021 |
Sensitivity analysis of the contractor’s financial effects achieved on a single building site H Anysz, W Rogala Scientific Review – Engineering and Environmental Sciences 28, 183-191, 2019 | 13 | 2019 |
Managing Delays in Construction Projects Aiming at Cost Overrun Minimization H Anysz IOP Conf. Series: Materials Science and Engineering, 2019 | 9 | 2019 |
The methodology of technical due diligence report preparation for an office, residential and industrial buildings B Kutera, H Anysz MATEC Web of Conferences 86, 07009, 2016 | 9 | 2016 |
Collusion and bid rigging in the construction industry: case studies from Poland A Foremny, J Kulejewski, H Anysz, A Nicał Építészmérnöki Kar, 2018 | 7 | 2018 |