| Long-term monitoring and data analysis of the Tamar Bridge EJ Cross, KY Koo, JMW Brownjohn, K Worden Mechanical Systems and Signal Processing 35 (1-2), 16-34, 2013 | 464 | 2013 |
| Cointegration: a novel approach for the removal of environmental trends in structural health monitoring data EJ Cross, K Worden, Q Chen Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2011 | 284 | 2011 |
| On robust regression analysis as a means of exploring environmental and operational conditions for SHM data N Dervilis, K Worden, EJ Cross Journal of Sound and Vibration 347, 279-296, 2015 | 169 | 2015 |
| Features for damage detection with insensitivity to environmental and operational variations EJ Cross, G Manson, K Worden, SG Pierce Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2012 | 159 | 2012 |
| Foundations of population-based SHM, Part I: Homogeneous populations and forms LA Bull, PA Gardner, J Gosliga, TJ Rogers, N Dervilis, EJ Cross, ... Mechanical systems and signal processing 148, 107141, 2021 | 151 | 2021 |
| On switching response surface models, with applications to the structural health monitoring of bridges K Worden, EJ Cross Mechanical Systems and Signal Processing 98, 139-156, 2018 | 119 | 2018 |
| A Bayesian non-parametric clustering approach for semi-supervised structural health monitoring TJ Rogers, K Worden, R Fuentes, N Dervilis, UT Tygesen, EJ Cross Mechanical Systems and Signal Processing 119, 100-119, 2019 | 93 | 2019 |
| Linear approaches to modeling nonlinearities in long-term monitoring of bridges E Figueiredo, E Cross Journal of Civil Structural Health Monitoring 3, 187-194, 2013 | 88 | 2013 |
| Improving aircraft performance using machine learning: A review S Le Clainche, E Ferrer, S Gibson, E Cross, A Parente, R Vinuesa Aerospace Science and Technology 138, 108354, 2023 | 85 | 2023 |
| Probabilistic modelling of wind turbine power curves with application of heteroscedastic Gaussian process regression TJ Rogers, P Gardner, N Dervilis, K Worden, AE Maguire, E Papatheou, ... Renewable Energy 148, 1124-1136, 2020 | 84 | 2020 |
| Prediction of landing gear loads using machine learning techniques G Holmes, P Sartor, S Reed, P Southern, K Worden, E Cross Structural Health Monitoring 15 (5), 568-582, 2016 | 80 | 2016 |
| Robust methods of inclusive outlier analysis for structural health monitoring N Dervilis, EJ Cross, RJ Barthorpe, K Worden Journal of Sound and Vibration 333 (20), 5181-5195, 2014 | 74 | 2014 |
| Probabilistic active learning: an online framework for structural health monitoring LA Bull, TJ Rogers, C Wickramarachchi, EJ Cross, K Worden, N Dervilis Mechanical Systems and Signal Processing 134, 106294, 2019 | 71 | 2019 |
| Machine learning at the interface of structural health monitoring and non-destructive evaluation P Gardner, R Fuentes, N Dervilis, C Mineo, SG Pierce, EJ Cross, ... Philosophical Transactions of the Royal Society A 378 (2182), 20190581, 2020 | 69 | 2020 |
| Artificial neural networks K Worden, G Tsialiamanis, EJ Cross, TJ Rogers Machine Learning in Modeling and Simulation: Methods and Applications, 85-119, 2023 | 67 | 2023 |
| A multiresolution approach to cointegration for enhanced SHM of structures under varying conditions–an exploratory study K Worden, EJ Cross, I Antoniadou, A Kyprianou Mechanical Systems and Signal Processing 47 (1-2), 243-262, 2014 | 66 | 2014 |
| On evolutionary system identification with applications to nonlinear benchmarks K Worden, RJ Barthorpe, EJ Cross, N Dervilis, GR Holmes, G Manson, ... Mechanical Systems and Signal Processing 112, 194-232, 2018 | 65 | 2018 |
| A regime-switching cointegration approach for removing environmental and operational variations in structural health monitoring H Shi, K Worden, EJ Cross Mechanical Systems and Signal Processing 103, 381-397, 2018 | 65 | 2018 |
| On structural health monitoring in changing environmental and operational conditions E Cross University of Sheffield, 2012 | 64 | 2012 |
| On the application of Gaussian process latent force models for joint input-state-parameter estimation: With a view to Bayesian operational identification TJ Rogers, K Worden, EJ Cross Mechanical Systems and Signal Processing 140, 106580, 2020 | 61 | 2020 |
Keith WordenUniversity of SheffieldVerified email at sheffield.ac.uk
