| Landslide susceptibility hazard map in southwest Sweden using artificial neural network AA Shahri, J Spross, F Johansson, S Larsson Catena 183, 104225, doi:10.1016/j.catena.2019.104225, 2019 | 203 | 2019 |
| Updating the neural network sediment load models using different sensitivity analysis methods: a regional application R Asheghi, SA Hosseini, M Saneie, A Abbaszadeh Shahri Journal of Hydroinformatics, doi:10.2166/hydro.2020.098, 2020 | 165 | 2020 |
| A novel approach to uncertainty quantification in groundwater table modeling by automated predictive deep learning A Abbaszadeh Shahri, C Shan, S Larsson Natural Resources Research 31, 1351–1373,DOI:10.1007/s11053-022-10051-w, 2022 | 124 | 2022 |
| An artificial neural network based model to predict spatial soil type distribution using piezocone penetration test data (CPTu) A Ghadri, AA Shahri, S Larson Bulletin of Engineering Geology and the Environment 78 (6), 4579–4588, doi …, 2019 | 99 | 2019 |
| Prediction of uniaxial compressive strength of different quarried rocks using metaheuristic algorithm R Asheghi, AA Shahri, MK Zak Arabian Journal for Science and Engineering 44 (10), 8645-8659, 2019 | 62 | 2019 |
| A visualized hybrid intelligent model to delineate Swedish fine-grained soil layers using clay sensitivity A Ghaderi, AA Shahri, S Larsson Catena 214, 106289, 2022 | 55 | 2022 |
| Landslide susceptibility mapping using hybridized block modular intelligence model AA Shahri, FM Moud Bulletin of Engineering Geology and the Environment 80, 267–284, DOI: 10 …, 2021 | 55 | 2021 |
| Optimized developed artificial neural network-based models to predict the blast-induced ground vibration A Abbaszadeh Shahri, R Asheghi Innovative Infrastructure Solutions 3 (doi: 10.1007/s41062-018-0137-4), 34, 2018 | 55 | 2018 |
| Assessment and prediction of liquefaction potential using different artificial neural network models - A case study AA Shahri Geotechnical and Geological Engineering, 34 (3), 807-815, doi:10.1007/s10706 …, 2016 | 54 | 2016 |
| A hybrid ensemble-based automated deep learning approach to generate 3D geo-models and uncertainty analysis A Abbaszadeh Shahri, S Chunling, S Larsson Engineering with Computers, 1501–1516, 2024, 2024 | 48 | 2024 |
| Soil classification analysis based on piezocone penetration test data—a case study from a quick-clay landslide site in southwestern Sweden AA Shahri, A Malehmir, C Juhlin Engineering Geology 189, 32-47, doi:10.1016/j.enggeo.2015.01.022, 2015 | 48 | 2015 |
| Artificial intelligence models to generate visualized bedrock level: a case study in Sweden A Abbaszadeh Shahri, S Larsson, C Renkel Modeling Earth Systems and Environment 6 (doi: 10.1007/s40808-020-00767-0 …, 2020 | 47 | 2020 |
| Spatial distribution modeling of subsurface bedrock using a developed automated intelligence deep learning procedure: A case study in Sweden AA Shahri, C Shan, E Zäll, S Larsson Journal of Rock Mechanics and Geotechnical Engineering 13 (6), 1300-1310, 2021 | 45 | 2021 |
| A hybrid computing model to predict rock strength index properties using support vector regression A Abbaszadeh Shahri, F Maghsoudi Moud, SP Mirfallah Lialestani Engineering with Computers, 1-16, DOI: 10.1007/s00366-020-01078-9, 2020 | 43 | 2020 |
| An optimized artificial neural network structure to predict clay sensitivity in a high landslide prone area using piezocone penetration test (CPTu) data- A case study in … AA Shahri Geotechnical and Geological Engineering 34 (2), 745-758, doi:10.1007/s10706 …, 2016 | 43 | 2016 |
| Prediction of bedload transport rate using a block combined network structure SA Hosseini, A Abbaszadeh Shahri, R Asheghi Hydrological Sciences Journal 67 (1), 117-128, doi: 10.1080/02626667.2021.2003, 2022 | 40 | 2022 |
| A hybridized intelligence model to improve the predictability level of strength index parameters of rocks A Abbaszadeh Shahri, R Asheghi, M Khorsand Zak Neural Computing and Applications 33, 3841–3854,DOI:10.1007/s00521-020-05223-9, 2021 | 40 | 2021 |
| Updated relations for the uniaxial compressive strength of marlstones based on P-wave velocity and point load index test A Abbaszadeh Shahri, S Larson, F Johansson Innovative Infrastructure Solutions 1, 17, doi:10.1007/s41062-016-0016-9, 2016 | 40 | 2016 |
| Automated intelligent hybrid computing schemes to predict blasting induced ground vibration A Abbaszadeh Shahri, F Pashamohammadi, R Asheghi, ... Engineering with Computers 38, 3335–3349, doi: 10.1007/s00366-021-01, 2022 | 36 | 2022 |
| A modified firefly algorithm applying on multi-objective radial-based function for blasting A Abbaszadeh Shahri, M Khorsand Zak, H Abbaszadeh Shahri Neural Computing and Applications 34, 2455–2471, DOI: 10.1007/s00521-021-06544, 2022 | 32 | 2022 |
Stefan LarssonProfessor in Geotechnology KTH Royal Institute of TechnologyE-mailová adresa ověřena na: byv.kth.se