Non‐parametric probabilistic forecasts of wind power: required properties and evaluation P Pinson, HA Nielsen, JK Møller, H Madsen, GN Kariniotakis Wind Energy: An International Journal for Progress and Applications in Wind …, 2007 | 395 | 2007 |
Time-adaptive quantile regression JK Møller, HA Nielsen, H Madsen Computational Statistics & Data Analysis 52 (3), 1292-1303, 2008 | 162 | 2008 |
Short-term probabilistic forecasting of wind speed using stochastic differential equations EB Iversen, JM Morales, JK Møller, H Madsen International Journal of Forecasting 32 (3), 981-990, 2016 | 136 | 2016 |
Probabilistic forecasts of solar irradiance using stochastic differential equations EB Iversen, JM Morales, JK Møller, H Madsen Environmetrics 25 (3), 152-164, 2014 | 100 | 2014 |
Inhomogeneous Markov models for describing driving patterns EB Iversen, JK Møller, JM Morales, H Madsen IEEE Transactions on Smart Grid 8 (2), 581-588, 2016 | 80 | 2016 |
From state dependent diffusion to constant diffusion in stochastic differential equations by the Lamperti transform JK Møller, H Madsen Technical University of Denmark, DTU Informatics, Building 321, 2010 | 67 | 2010 |
An introduction to multivariate probabilistic forecast evaluation MB Bjerregård, JK Møller, H Madsen Energy and AI 4, 100058, 2021 | 49 | 2021 |
Probabilistic forecasts of wind power generation by stochastic differential equation models JK Møller, M Zugno, H Madsen Journal of Forecasting 35 (3), 189-205, 2016 | 47 | 2016 |
Hidden Markov Models for indirect classification of occupant behaviour J Liisberg, JK Møller, H Bloem, J Cipriano, G Mor, H Madsen Sustainable Cities and Society 27, 83-98, 2016 | 44 | 2016 |
A Markov-Switching model for building occupant activity estimation S Wolf, JK Møller, MA Bitsch, J Krogstie, H Madsen Energy and Buildings 183, 672-683, 2019 | 42 | 2019 |
Grey‐box modelling of flow in sewer systems with state‐dependent diffusion A Breinholt, FÖ Thordarson, JK Møller, M Grum, PS Mikkelsen, H Madsen Environmetrics 22 (8), 946-961, 2011 | 39 | 2011 |
Recent developments in multivariate wind and solar power forecasting ML Sørensen, P Nystrup, MB Bjerregård, JK Møller, P Bacher, H Madsen Wiley Interdisciplinary Reviews: Energy and Environment 12 (2), e465, 2023 | 38 | 2023 |
Prioritize effluent quality, operational costs or global warming?–using predictive control of wastewater aeration for flexible management of objectives in WRRFs PA Stentoft, T Munk-Nielsen, JK Møller, H Madsen, B Valverde-Pérez, ... Water Research 196, 116960, 2021 | 37 | 2021 |
ctsmr-continuous time stochastic modeling in R R Juhl, JK Møller, H Madsen arXiv preprint arXiv:1606.00242, 2016 | 36 | 2016 |
Towards model predictive control: online predictions of ammonium and nitrate removal by using a stochastic ASM PA Stentoft, T Munk-Nielsen, L Vezzaro, H Madsen, PS Mikkelsen, ... Water Science and Technology 79 (1), 51-62, 2019 | 35 | 2019 |
Heat load forecasting using adaptive temporal hierarchies HG Bergsteinsson, JK Møller, P Nystrup, ÓP Pálsson, D Guericke, ... Applied Energy 292, 116872, 2021 | 34 | 2021 |
Leveraging stochastic differential equations for probabilistic forecasting of wind power using a dynamic power curve EB Iversen, JM Morales, JK Møller, PJ Trombe, H Madsen Wind Energy 20 (1), 33-44, 2017 | 34 | 2017 |
Probabilistic load forecasting considering temporal correlation: Online models for the prediction of households’ electrical load J Lemos-Vinasco, P Bacher, JK Møller Applied Energy 303, 117594, 2021 | 29 | 2021 |
Cross-validation of a glucose-insulin-glucagon pharmacodynamics model for simulation using data from patients with type 1 diabetes SL Wendt, A Ranjan, JK Møller, S Schmidt, CB Knudsen, JJ Holst, ... Journal of diabetes science and technology 11 (6), 1101-1111, 2017 | 29 | 2017 |
A formal statistical approach to representing uncertainty in rainfall–runoff modelling with focus on residual analysis and probabilistic output evaluation–Distinguishing … A Breinholt, JK Møller, H Madsen, PS Mikkelsen Journal of hydrology 472, 36-52, 2012 | 28 | 2012 |