Scaling and blockage risk in geothermal reinjection wellbore: Experiment assessment and model prediction based on scaling deposition kinetics

2021 ◽  
pp. 109867
Author(s):  
Liang Zhang ◽  
Songhe Geng ◽  
Jiahao Chao ◽  
Linchao Yang ◽  
Zhen Zhao ◽  
...  
Keyword(s):  
Model Prediction ◽  
Deposition Kinetics

Turnaround Model Prediction with Content Dimension on Financial Distress Firms

2020 ◽  
Vol 11 (1) ◽  
pp. 65-65
Author(s):  
Giriati
Keyword(s):  
Family Member ◽  
Model Prediction ◽  
Significant Relationship ◽  
Financial Distress ◽  
Stock Exchange ◽  
Organization Change ◽  
Least Square ◽  
Ordinary Least Square ◽  
Change Framework

This article aims to synthesize and test empirically turnaround model by content dimension that is an integration of the organization change framework into turnaround research to measure some activities done to avoid failure in turnaround. This study on the Indonesian Stock Exchange (BEI) by using Ordinary Least Square technique. The results of the analysis from content dimension show that the CEO expertise variable has a significant relationship to turnaround, since companies in Indonesia are dominated by family companies, so maintaining the incumbent CEO is more appropriate, because it is a family member. In addition, free assets show a significant relationship with turnaround, while leverage and growth of sales do not have a significant relationship with turnaround. Keywords: Financial Distress, Turnaround Model, CEO Expertise, Free Assets, Leverage and Growth of Sales,

Fiction and reality in the modelling world-balance between simplicity and complexity, calibration and identifiability, verification and falsification

1999 ◽  
Vol 39 (9) ◽  
pp. 1-8 ◽  
Author(s):  
P. Harremoës ◽  
H. Madsen
Keyword(s):  
Model Prediction ◽  
Model Performance ◽  
Data Series ◽  
Urban Drainage ◽  
Model Structure ◽  
And Control

Where is the balance between simplicity and complexity in model prediction of urban drainage structures? The calibration/verification approach to testing of model performance gives an exaggerated sense of certainty. Frequently, the model structure and the parameters are not identifiable by calibration/verification on the basis of the data series available, which generates elements of sheer guessing - unless the universality of the model is be based on induction, i.e. experience from the sum of all previous investigations. There is a need to deal more explicitly with uncertainty and to incorporate that in the design, operation and control of urban drainage structures.

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