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 Henrik Madsen

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Publication count18
Publication years1994-2016
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18 results found Export Results: bibtexendnoteacmrefcsv

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1
November 2016 Computers and Operations Research: Volume 75 Issue C, November 2016
Publisher: Elsevier Science Ltd.
Bibliometrics:
Citation Count: 0

The joint management of heat and power systems is believed to be key to the integration of renewables into energy systems with a large penetration of district heating. Determining the day-ahead unit commitment and production schedules for these systems is an optimization problem subject to uncertainty stemming from the unpredictability ...
Keywords: OR in energy, Robust optimization, Decision rules, Energy market, Combined heat and power

2
June 2016 Environmental Modelling & Software: Volume 80 Issue C, June 2016
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 1

This article demonstrates the incorporation of stochastic grey-box models for urban runoff forecasting into a full-scale, system-wide control setup where setpoints are dynamically optimized considering forecast uncertainty and sensitivity of overflow locations in order to reduce combined sewer overflow risk. The stochastic control framework and the performance of the runoff ...
Keywords: Real-time control, Stochastic grey-box model, Storm water management, Probabilistic forecasting, Radar rainfall, Urban hydrology

3
January 2012 ISGT '12: Proceedings of the 2012 IEEE PES Innovative Smart Grid Technologies
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 3

Model Predictive Control (MPC) can be used to control a system of energy producers and consumers in a Smart Grid. In this paper, we use heat pumps for heating residential buildings with a floor heating system. We use the thermal capacity of the building to shift the energy consumption to ...

4
January 2011 Computational Statistics & Data Analysis: Volume 55 Issue 1, January, 2011
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 2

A new approach to nonlinear state estimation and object tracking from indirect observations of a continuous time process is examined. Stochastic differential equations (SDEs) are employed to model the dynamics of the unobservable state. Tracking problems in the plane subject to boundaries on the state-space do not in general provide ...
Keywords: Finite element method, Point-mass filter, Sequential Monte Carlo, Nonlinear state estimation, Hidden Markov model, Stochastic differential equation

5
June 2009 Computer Methods and Programs in Biomedicine: Volume 94 Issue 3, June, 2009
Publisher: Elsevier North-Holland, Inc.
Bibliometrics:
Citation Count: 2

The extension from ordinary to stochastic differential equations (SDEs) in pharmacokinetic and pharmacodynamic (PK/PD) modelling is an emerging field and has been motivated in a number of articles [N.R. Kristensen, H. Madsen, S.H. Ingwersen, Using stochastic differential equations for PK/PD model development, J. Pharmacokinet. Pharmacodyn. 32 (February(1)) (2005) 109-141; C.W. ...
Keywords: Mixed-effect, Pharmacodynamic, State-space models, Stochastic differential equations (SDEs), Pharmacokinetic

6
November 2008 Expert Systems with Applications: An International Journal: Volume 35 Issue 4, November, 2008
Publisher: Pergamon Press, Inc.
Bibliometrics:
Citation Count: 0

In the year 2006 about 4000 farms worldwide used over 6000 milking robots. With increased automation the time that the cattle keeper uses for monitoring animals has decreased. This has created a need for automatic health monitoring systems. Lameness is a crucial welfare and economic issue in modern dairy husbandry. ...
Keywords: Lameness detection, Livestock weighing, Statistical quality control, Dairy cattle

7
March 2008 Statistics and Computing: Volume 18 Issue 1, March 2008
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 3

Short-term forecasting of wind generation requires a model of the function for the conversion of meteorological variables (mainly wind speed) to power production. Such a power curve is nonlinear and bounded, in addition to being nonstationary. Local linear regression is an appealing nonparametric approach for power curve estimation, for which ...
Keywords: Local linear regression, Total least squares, Adaptive estimation, Modelling, Forecasting, Nonparametric regression, Robust estimation, Wind power

8
January 2008 Computational Statistics & Data Analysis: Volume 52 Issue 3, January, 2008
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 4

An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method and an updating procedure are ...
Keywords: Wind power, Quantile regression, Simplex, Time-adaptive

9
July 2005 Future Generation Computer Systems: Volume 21 Issue 7, July 2005
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 2

The Kalman filter is a sequential estimation procedure that combines a stochastic dynamical model with observations in order to update the model state and the associated uncertainty. In the situation where no measurements are available the filter works as an uncertainty propagator. The most computationally demanding part of the Kalman ...
Keywords: Kalman filter, Lanczos algorithm, RRSQRT, Reduced rank square-root

10
February 2004 Automatica (Journal of IFAC): Volume 40 Issue 2, February, 2004
Publisher: Pergamon Press, Inc.
Bibliometrics:
Citation Count: 9

An efficient and flexible parameter estimation scheme for grey-box models in the sense of discretely, partially observed Ito stochastic differential equations with measurement noise is presented along with a corresponding software implementation. The estimation scheme is based on the extended Kalman filter and features maximum likelihood as well as maximum ...
Keywords: Extended Kalman filter, Grey-box models, Robust estimation, Software tools, Stochastic differential equations, Estimation accuracy, Estimation with missing observations, Maximum likelihood estimation, Parameter estimation

11
June 2003 ICCS'03: Proceedings of the 1st international conference on Computational science: PartI
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

The reduced rank square root filter is a special formulation of the Kalman filter for assimilation of data in large scale models that represent simple linear or complex nonlinear systems. In this formulation, the covariance matrix of the model state is expressed in a limited number of modes. In the ...

12
July 2001 Computational Statistics & Data Analysis: Volume 37 Issue 1, July, 2001
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 3

In classical time series analysis the sample autocorrelation function (SACF) and the sample partial autocorrelation function (SPACF) has gained wide application for structural identification of linear time series models. We suggest generalizations, founded on smoothing techniques, applicable for structural identification of non-linear time series models. A similar generalization of the ...
Keywords: Non-linear time series, R-squared, Bootstrap., Lagged scatter plot, Smoothing, Independence, Non-parametric

13
January 2001 Automatica (Journal of IFAC): Volume 37 Issue 1, January, 2001
Publisher: Pergamon Press, Inc.
Bibliometrics:
Citation Count: 3

A transformation is introduced to effectively remove level effects, i.e. the state dependency of the diffusion function, in a restricted class of multivariate stochastic differential equations such that the general continuous-discrete-time nonlinear filtering problem may be solved using new or existing implementations of the extended kalman filter (EKF). An implementation ...
Keywords: Brownian motion, Extended Kalman filters, Stochastic differential equations, Continuous-time systems, Maximum likelihood estimation, Stochastic modelling

14
December 2000 International Journal of Adaptive Control and Signal Processing: Volume 14 Issue 8, December 2000
Publisher: John Wiley & Sons, Inc.
Bibliometrics:
Citation Count: 0

A method for adaptive and recursive estimation in a class of non-linear autoregressive models with external input is proposed. The model class considered is conditionally parametric ARX-models CPARX-models, which is conventional ARX-models in which the parameters are replaced by smooth, but otherwise unknown, functions of a low-dimensional input process. These ...
Keywords: non-parametric method, adaptive and recursive estimation, conditional parametric models, non-linear models, time-varying functions

15
August 2000 Automatica (Journal of IFAC): Volume 36 Issue 8, August, 2000
Publisher: Pergamon Press, Inc.
Bibliometrics:
Citation Count: 1

This paper shows that the recursive least-squares (RLS) algorithm with forgetting factor is a special case of a varying-coefficient model, and a model which can easily be estimated via simple local regression. This observation allows us to formulate a new method which retains the RLS algorithm, but extends the algorithm ...
Keywords: Recursive estimation, Varying-coefficient, Weighting functions, Conditional parametric, Polynomial approximation

16
November 1995 International Journal of Adaptive Control and Signal Processing: Volume 9 Issue 6, November 1995
Publisher: John Wiley & Sons, Inc.
Bibliometrics:
Citation Count: 0

Grey box models are characterized by their physical significance e.g. in parametrization and by the partial prior information that is available about e.g. the parameter values. These aspects of the grey box model affect the design of optimal excitations for identification and we study the extension of classical theory for ...
Keywords: grey box identification, Bayesian criterion, experiment design, physical models

17
December 1994 Automatica (Journal of IFAC): Volume 30 Issue 12, Dec. 1994
Publisher: Pergamon Press, Inc.
Bibliometrics:
Citation Count: 0

Keywords: time-varying systems, generalized predictive control, filtering, impulse response

18
June 1994 Computational Statistics & Data Analysis: Volume 17 Issue 5, June 1994
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 1

Keywords: robust estimation, time series analysis, additive and innovation outliers, recursive estimation, bounded-influence estimation



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