On-line measurement-based model parameter estimation for synchronous generators: solution algorithm and numerical studies

1994 ◽  
Vol 9 (2) ◽  
pp. 337-343 ◽  
Author(s):  
Jin-Cheng Wang ◽  
Hsiao-Dong Chiang ◽  
Chiang-Tsung Huang ◽  
Yung-Tien Chen ◽  
Chung-Liang Chang ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Solution Algorithm ◽  
Synchronous Generators ◽  
Model Parameter ◽  
Model Parameter Estimation ◽  
Numerical Studies ◽  
Line Measurement ◽  
On Line

On-line measurement-based model parameter estimation for synchronous generators: model development and identification schemes

1994 ◽  
Vol 9 (2) ◽  
pp. 330-336 ◽  
Author(s):  
Chiang-Tsung Huang ◽  
Yung-Tien Chen ◽  
Chung-Liang Chang ◽  
Chiung-Yi Huang ◽  
Hsiao-Dong Chiang ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Model Development ◽  
Synchronous Generators ◽  
Model Parameter ◽  
Model Parameter Estimation ◽  
Identification Schemes ◽  
Line Measurement ◽  
On Line

Respirometry-based on-line model parameter estimation at a full-scale WWTP

2002 ◽  
Vol 45 (4-5) ◽  
pp. 335-343 ◽  
Author(s):  
H. Spanjers ◽  
G.G. Patry ◽  
K.J. Keesman
Keyword(s):  
Wastewater Treatment ◽  
Parameter Estimation ◽  
Activated Sludge ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Parameter Estimates ◽  
Model Parameter ◽  
Model Parameter Estimation ◽  
On Line ◽  
Set Up

This paper describes part of a project to develop a systematic approach to knowledge extraction from on-line respirometric measurements in support of wastewater treatment plant control and operation. The paper deals with the following issues: (1) test of the implementation of an automatic set-up consisting of a continuous laboratory respirometer integrated in a mobile trailer with sampling and dosing equipment, and data-acquisition and communication system; (2) assessment of activated sludge/sewage characteristics from sludge respirograms by model parameter estimation; (3) comparison of the parameter estimates with regular plant data and information obtained from supplementary wastewater respirograms. The paper describes the equipment and some of its measuring results from a period of one week at a large-scale wastewater treatment plant. The measurements were evaluated in terms of the common activated sludge modelling practice. The automatic set-up allowed reliable measurements during at least one week. The data were used to calibrate two different version of the model, and independent parameter estimates were obtained.

l2-Penalized temporal logit-mixed models for the estimation of regional obesity prevalence over time

2021 ◽  
pp. 096228022110175
Author(s):  
Jan P Burgard ◽  
Joscha Krause ◽  
Ralf Münnich ◽  
Domingo Morales
Keyword(s):  
Parameter Estimation ◽  
Medical Treatment ◽  
Mixed Models ◽  
Generalized Linear Mixed Models ◽  
Linear Mixed Models ◽  
Obesity Prevalence ◽  
Model Parameter ◽  
Model Parameter Estimation ◽  
Public Health Reporting ◽  
Over Time

Obesity is considered to be one of the primary health risks in modern industrialized societies. Estimating the evolution of its prevalence over time is an essential element of public health reporting. This requires the application of suitable statistical methods on epidemiologic data with substantial local detail. Generalized linear-mixed models with medical treatment records as covariates mark a powerful combination for this purpose. However, the task is methodologically challenging. Disease frequencies are subject to both regional and temporal heterogeneity. Medical treatment records often show strong internal correlation due to diagnosis-related grouping. This frequently causes excessive variance in model parameter estimation due to rank-deficiency problems. Further, generalized linear-mixed models are often estimated via approximate inference methods as their likelihood functions do not have closed forms. These problems combined lead to unacceptable uncertainty in prevalence estimates over time. We propose an l2-penalized temporal logit-mixed model to solve these issues. We derive empirical best predictors and present a parametric bootstrap to estimate their mean-squared errors. A novel penalized maximum approximate likelihood algorithm for model parameter estimation is stated. With this new methodology, the regional obesity prevalence in Germany from 2009 to 2012 is estimated. We find that the national prevalence ranges between 15 and 16%, with significant regional clustering in eastern Germany.

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