Monitoring parameter changes in models with a trend

2020 ◽  
Vol 207 ◽  
pp. 288-319
Author(s):  
Peiyun Jiang ◽  
Eiji Kurozumi
Keyword(s):  
Monitoring Parameter

scholarly journals Correction on “Towards Detecting Swath Events in TerraSAR-X Time Series to Establish NATURA 2000 Grassland Habitat Swath Management as Monitoring Parameter”

2012 ◽  
Vol 4 (8) ◽  
pp. 2455-2456 ◽  
Author(s):  
Christian Schuster ◽  
Iftikhar Ali ◽  
Peter Lohmann ◽  
Annett Frick ◽  
Michael Förster ◽  
...  
Keyword(s):  
Time Series ◽  
Natura 2000 ◽  
Monitoring Parameter

scholarly journals Application of Various Machine Learning Models for Process Stability of Bio-Electrochemical Anaerobic Digestion

Processes ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 158
Author(s):  
Ain Cheon ◽  
Jwakyung Sung ◽  
Hangbae Jun ◽  
Heewon Jang ◽  
Minji Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Anaerobic Digestion ◽  
Prediction Accuracy ◽  
Input Data ◽  
Process Stability ◽  
Operational Parameters ◽  
Monitoring Parameter ◽  
Efficient Prediction ◽  
Single Input ◽  
Machine Learning Models

The application of a machine learning (ML) model to bio-electrochemical anaerobic digestion (BEAD) is a future-oriented approach for improving process stability by predicting performances that have nonlinear relationships with various operational parameters. Five ML models, which included tree-, regression-, and neural network-based algorithms, were applied to predict the methane yield in BEAD reactor. The results showed that various 1-step ahead ML models, which utilized prior data of BEAD performances, could enhance prediction accuracy. In addition, 1-step ahead with retraining algorithm could improve prediction accuracy by 37.3% compared with the conventional multi-step ahead algorithm. The improvement was particularly noteworthy in tree- and regression-based ML models. Moreover, 1-step ahead with retraining algorithm showed high potential of achieving efficient prediction using pH as a single input data, which is plausibly an easier monitoring parameter compared with the other parameters required in bioprocess models.

scholarly journals Towards Detecting Swath Events in TerraSAR-X Time Series to Establish NATURA 2000 Grassland Habitat Swath Management as Monitoring Parameter

2011 ◽  
Vol 3 (7) ◽  
pp. 1308-1322 ◽  
Author(s):  
Christian Schuster ◽  
Iftikhar Ali ◽  
Peter Lohmann ◽  
Annett Frick ◽  
Michael Förster ◽  
...  
Keyword(s):  
Time Series ◽  
Natura 2000 ◽  
Monitoring Parameter

Expression of HLA Molecules on Peripheral Blood Lymphocytes: A Useful Monitoring Parameter in Cardiac Transplantation

2007 ◽  
Vol 39 (7) ◽  
pp. 2362-2364 ◽  
Author(s):  
R.M. Blanco-Garcia ◽  
M.R. López-Álvarez ◽  
D.A. Pascual-Figal ◽  
L. Polo-Garcia ◽  
N. Guerra ◽  
...  
Keyword(s):  
Peripheral Blood ◽  
Cardiac Transplantation ◽  
Peripheral Blood Lymphocytes ◽  
Blood Lymphocytes ◽  
Monitoring Parameter ◽  
Hla Molecules

Neopterin as a monitoring parameter for treatment with BCG in superficial bladder cancer

1995 ◽  
Vol 31 (6) ◽  
pp. 1025-1026 ◽  
Author(s):  
D. Mack ◽  
A. Gomahr ◽  
M. Herold ◽  
J. Frick
Keyword(s):  
Bladder Cancer ◽  
Superficial Bladder Cancer ◽  
Monitoring Parameter

scholarly journals Condition Monitoring of Forward Curved Centrifugal Blower Using Coast Down Time Analysis

2010 ◽  
Vol 2010 ◽  
pp. 1-12
Author(s):  
G. R. Rameshkumar ◽  
B. V. A. Rao ◽  
K. P. Ramachandran
Keyword(s):  
Condition Monitoring ◽  
Health Condition ◽  
Centrifugal Blower ◽  
Rotating Machine ◽  
Monitoring Parameter ◽  
Shaft Misalignment ◽  
Sustained Operation ◽  
Mechanical Faults ◽  
Machine Health ◽  
Reduction Percentage

Mechanical malfunctions such as, rotor unbalance and shaft misalignment are the most common causes of vibration in rotating machineries. Vibration is the most widely used parameter to monitor and asses the machine health condition. In this work, the Coast Down Time (CDT), which is an indicator of faults, is used to assess the condition of the rotating machine as a condition monitoring parameter. CDT is the total time taken by the system to dissipate the momentum acquired during sustained operation. Extensive experiments were conducted on Forward Curved Centrifugal Blower Test Rig at selected cutoff speeds for several combinations of combined horizontal and vertical parallel misalignment, combined parallel and angular misalignment, as well as for various unbalance conditions. As mechanical faults increase, a drastic decrease in CDT is found and this is represented as CDT reduction percentage. A specific correlation between the CDT reduction percentage, level of mechanical faults, and rotational cutoff speeds is observed. The results are analyzed and compared with vibration analysis for potential use of CDT as one of the condition monitoring parameter.

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