Author Correction: Revelation of early detection of co-seismic ionospheric perturbations in GPS-TEC from realistic modelling approach: Case study

The paper illustrates analysis of the assumptions of the statistical component of a hybrid modelling approach for predicting environmental extremes. This shows how to assess the applicability of the approach to water quality problems. The analysis involves data on stream acidity from the Birkenes catchment in Norway. The modelling approach is hybrid in that it uses: (1) a deterministic or process-based description to simulate (non-stationary) long term trend values of environmental variables, and (2) probability distributions which are superimposed on the trend values to characterise the frequency of shorter term concentrations. This permits assessment of management strategies and of sensitivity to climate variables by adjusting the values of major forcing variables in the trend model. Knowledge of the variability about the trend is provided by: (a) identification of an appropriate parametric form of the probability density function (pdf) of the environmental attribute (e.g. stream acidity variables) whose extremes are of interest, and (b) estimation of pdf parameters using the output of the trend model.

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Understanding effect site pharmacology of uprifosbuvir, a HCV nucleoside inhibitor: case study of a multidisciplinary modelling approach in drug development

CPT Pharmacometrics & Systems Pharmacology ◽

10.1002/psp4.12644 ◽

2021 ◽

Author(s):

Paul van den Berg ◽

Wei Gao ◽

Maurice J. Ahsman ◽

Leticia Arrington ◽

Filippos Kesisoglou ◽

...

Keyword(s):

Drug Development ◽

Effect Site ◽

Modelling Approach

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An interpretative structural modelling approach to analysing root causes of defective jobs: a case study in an automobile service industry

International Journal of Productivity and Quality Management ◽

10.1504/ijpqm.2020.109327 ◽

2020 ◽

Vol 31 (1) ◽

pp. 1

Author(s):

Dharyll Prince Abellana

Keyword(s):

Service Industry ◽

Structural Modelling ◽

Modelling Approach

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Descriptive variables and their role in predicting the financial position of Algerian companies: The case of a sample of Algerian companies

Journal of Finance & Corporate Governance ◽

10.54960/jfcg.v1i2.13 ◽

2017 ◽

Vol 1 (2) ◽

Author(s):

Khalid BENAMOR ◽

Wissam ABAI ◽

Lamdjed BOUZIDI

Keyword(s):

Early Detection ◽

Predictive Ability ◽

Remarkable Increase ◽

Financial Position ◽

Sample Data ◽

The Future ◽

Risk Scoring ◽

Positive Results

Despite positive results quantitative variables have had in predicting the future of companies alongside their predictive ability of companies’ financial position, the remarkable increase in bankruptcies of companies without any early detection and the consequent damage to the economy in general and to companies in particular, highlighted the need to make up for quantitative variables luck in terms of predictive significance in the process of predicting companies’ financial position, which made studies interested in this field react by emphasizing variables of descriptive nature. The aim of this study is to appreciate aspects of variables of descriptive nature and the extent of their contribution to the prediction of financial position of Algerian companies, using as a case study descriptive variables data of the risk scoring technique with application on a sample data of 15 companies operating in Algiers. This study concluded that descriptive variables contribute significantly to the prediction of the financial position of Algerian companies.

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Comparing an insurer's perspective on building damages with modelled damages from pan-European winter windstorm event sets: a case study from Zurich, Switzerland

Natural Hazards and Earth System Science ◽

10.5194/nhess-21-279-2021 ◽

2021 ◽

Vol 21 (1) ◽

pp. 279-299

Author(s):

Christoph Welker ◽

Thomas Röösli ◽

David N. Bresch

Keyword(s):

Open Source ◽

Return Period ◽

Model Building ◽

Information Service ◽

Source Model ◽

Insurance Companies ◽

Risk Models ◽

Risk Modelling ◽

Modelling Approach

Abstract. With access to claims, insurers have a long tradition of being knowledge leaders on damages caused by windstorms. However, new opportunities have arisen to better assess the risks of winter windstorms in Europe through the availability of historic footprints provided by the Windstorm Information Service (Copernicus WISC). In this study, we compare how modelling of building damages complements claims-based risk assessment. We describe and use two windstorm risk models: an insurer's proprietary model and the open source CLIMADA platform. Both use the historic WISC dataset and a purposefully built, probabilistic hazard event set of winter windstorms across Europe to model building damages in the canton of Zurich, Switzerland. These approaches project a considerably lower estimate for the annual average damage (CHF 1.4 million), compared to claims (CHF 2.3 million), which originates mainly from a different assessment of the return period of the most damaging historic event Lothar–Martin. Additionally, the probabilistic modelling approach allows assessment of rare events, such as a 250-year-return-period windstorm causing CHF 75 million in damages, including an evaluation of the uncertainties. Our study emphasizes the importance of complementing a claims-based perspective with a probabilistic risk modelling approach to better understand windstorm risks. The presented open-source model provides a straightforward entry point for small insurance companies.

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Application of data-based mechanistic modelling for flood forecasting at multiple locations in the Eden catchment in the National Flood Forecasting System (England and Wales)

Hydrology and Earth System Sciences ◽

10.5194/hess-17-177-2013 ◽

2013 ◽

Vol 17 (1) ◽

pp. 177-185 ◽

Cited By ~ 10

Author(s):

D. Leedal ◽

A. H. Weerts ◽

P. J. Smith ◽

K. J. Beven

Keyword(s):

Warning System ◽

Open Shell ◽

Flood Forecasting ◽

Mechanistic Modelling ◽

Forecasting Models ◽

Forecasting System ◽

Environment Agency ◽

The Uk ◽

Modelling Approach

Abstract. The Delft Flood Early Warning System provides a versatile framework for real-time flood forecasting. The UK Environment Agency has adopted the Delft framework to deliver its National Flood Forecasting System. The Delft system incorporates new flood forecasting models very easily using an "open shell" framework. This paper describes how we added the data-based mechanistic modelling approach to the model inventory and presents a case study for the Eden catchment (Cumbria, UK).

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