More information
Work
- Sabine Knapp & Michel van de Velden (2024) - Predicting inspection outcomes and evaluating port state control targeting using random forests - doi: 10.13140/RG.2.2.26683.43040
- Sabine Knapp & Michel van de Velden (2024) - Improved risk predictions of vessels using machine learning: how effective is the status quo?
- Sabine Knapp & Michel van de Velden (2023) - Exploration of machine learning methods for maritime risk predictions - Maritime Policy and Management, 51 (7), 1443-1473 - doi: 10.1080/03088839.2023.2209788 - [link]
- Philip Hans Franses & Sabine Knapp (2022) - Empirical analysis of the effectiveness of the legislative framework in the maritime industry - Marine Policy, 147 - doi: 10.1016/j.marpol.2022.105401 - [link]
- Sabine Knapp & Philip Hans Franses (2022) - Empirical analysis of the effectiveness of the legislative framework in the maritime industry - doi: 10.1016/j.marpol.2022.105401 - [link]
- Sabine Knapp & Michel van de Velden (2022) - Predicting detention and deficiencies using random forests
- Sabine Knapp, Philip Hans Franses & B Whitby (2020) - Measuring the effect of perceived corruption on detention and incident risk - an empirical analyses.
- Sabine Knapp (2020) - Quantification and analysis of risk exposure in the maritime industry: Averted incident costs due to inspections and the effect of SARS-CoV-2 (Covid19)
- Stephen Vander Hoorn & Sabine Knapp (2019) - Predicting traffic and risk exposure in the maritime industry - Safety, 5 (3) - doi: 10.3390/safety5030042 - [link]
- Sabine Knapp & Christiaan Heij (2019) - Improved strategies for the maritime industry to target vessels for inspection and to select inspection priority areas - [link]
