| Landslide susceptibility hazard map in southwest Sweden using artificial neural network AA Shahri, J Spross, F Johansson, S Larsson Catena 183, 104225, 2019 | 207 | 2019 |
| State of Practice Report–Execution, monitoring and quality control S Larsson Deep Mixing 5, 732-785, 2005 | 139 | 2005 |
| 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 (3), 1351-1373, 2022 | 126 | 2022 |
| Effect of basalt fiber inclusion on the mechanical properties and microstructure of cement-solidified kaolinite D Wang, H Wang, S Larsson, M Benzerzour, W Maherzi, M Amar Construction and Building Materials 241, 118085, 2020 | 111 | 2020 |
| On horizontal variability in lime-cement columns in deep mixing S Larsson, H Stille, L Olsson Géotechnique 55 (1), 33-44, 2005 | 109 | 2005 |
| Mixing processes for ground improvement by deep mixing S Larsson Byggvetenskap, 2003 | 106 | 2003 |
| An artificial neural network based model to predict spatial soil type distribution using piezocone penetration test data (CPTu) A Ghaderi, A Abbaszadeh Shahri, S Larsson Bulletin of Engineering Geology and the Environment 78, 4579-4588, 2019 | 101 | 2019 |
| Uniformity of lime-cement columns for deep mixing: a field study S Larsson, M Dahlström, B Nilsson Proceedings of the institution of civil engineers-ground improvement 9 (1), 1-15, 2005 | 93 | 2005 |
| Shear strength of partially bonded concrete–rock interfaces for application in dam stability analyses A Krounis, F Johansson, S Larsson Rock Mechanics and Rock Engineering 49 (7), 2711-2722, 2016 | 89 | 2016 |
| Bearing capacity and failure behaviors of floating stiffened deep cement mixing columns under axial load A Wonglert, P Jongpradist, P Jamsawang, S Larsson Soils and Foundations 58 (2), 446-461, 2018 | 82 | 2018 |
| Soil compaction by vibratory roller with variable frequency C Wersäll, I Nordfelt, S Larsson Géotechnique 67 (3), 272-278, 2017 | 69 | 2017 |
| Finite element modelling of laterally loaded lime–cement columns using a damage plasticity model S Larsson, R Malm, B Charbit, A Ansell Computers and Geotechnics 44, 48-57, 2012 | 63 | 2012 |
| Two-and three-dimensional analyses of excavation support with rows of dry deep mixing columns R Ignat, S Baker, S Larsson, S Liedberg Computers and Geotechnics 66, 16-30, 2015 | 57 | 2015 |
| 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 |
| Extended multivariate approach for uncertainty reduction in the assessment of undrained shear strength in clays R Müller, S Larsson, J Spross Canadian Geotechnical Journal 51 (3), 231-245, 2014 | 55 | 2014 |
| A laboratory study on strength loss in kaolin surrounding lime–cement columns S Larsson, M Rothhämel, G Jacks Applied Clay Science 44 (1-2), 116-126, 2009 | 52 | 2009 |
| 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 40 (3), 1501-1516, 2024 | 51 | 2024 |
| Effects of spatial variation in cohesion over the concrete-rock interface on dam sliding stability A Krounis, F Johansson, S Larsson Journal of Rock Mechanics and Geotechnical Engineering 7 (6), 659-667, 2015 | 49 | 2015 |
| Strength variability in lime-cement columns based on cone penetration test data MS Al-Naqshabandy, N Bergman, S Larsson Proceedings of the Institution of Civil Engineers-Ground Improvement 165 (1 …, 2012 | 49 | 2012 |
| 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 | 48 | 2021 |
Johan SprossResearcher at the Division of Soil and Rock Mechanics, KTH Royal Institute ofVerified email at byv.kth.se
