scholarly journals An efficient methodology for modeling complex computer codes with Gaussian processes

2008 ◽  
Vol 52 (10) ◽  
pp. 4731-4744 ◽  
Author(s):  
Amandine Marrel ◽  
Bertrand Iooss ◽  
François Van Dorpe ◽  
Elena Volkova
Keyword(s):  
Gaussian Processes ◽  
Computer Codes ◽  
Complex Computer

Sequential Experiment Design for Contour Estimation From Complex Computer Codes

Technometrics ◽  
2008 ◽  
Vol 50 (4) ◽  
pp. 527-541 ◽  
Author(s):  
Pritam Ranjan ◽  
Derek Bingham ◽  
George Michailidis
Keyword(s):  
Experiment Design ◽  
Contour Estimation ◽  
Computer Codes ◽  
Sequential Experiment ◽  
Complex Computer

scholarly journals Active emulation of computer codes with Gaussian processes – Application to remote sensing

2020 ◽  
Vol 100 ◽  
pp. 107103 ◽  
Author(s):  
Daniel Heestermans Svendsen ◽  
Luca Martino ◽  
Gustau Camps-Valls
Keyword(s):  
Remote Sensing ◽  
Gaussian Processes ◽  
Computer Codes

scholarly journals Black-box calibration for complex-system simulation

2010 ◽  
Vol 368 (1924) ◽  
pp. 3567-3579 ◽  
Author(s):  
Alexander I. J. Forrester
Keyword(s):  
Computer Models ◽  
Flow Solver ◽  
Unmanned Air Vehicle ◽  
Multiple Observations ◽  
Physical Experiments ◽  
Rear Wing ◽  
Air Vehicle ◽  
Computer Codes ◽  
Computationally Intensive ◽  
Complex Computer

Predicting or measuring the output of complex systems is an important and challenging part of many areas of science. If multiple observations are required for parameter studies and optimization, accurate, computationally intensive predictions or expensive experiments are intractable. This paper looks at the use of Gaussian-process-based correlations to correct simple computer models with sparse data from physical experiments or more complex computer models. In essence, physics-based computer codes and experiments are replaced by fast problem-specific statistics-based codes. Two aerodynamic design examples are presented. First, a cheap two-dimensional potential-flow solver is calibrated to represent the flow over the wing of an unmanned air vehicle. The rear wing of a racing car is then optimized using rear-wing simulations calibrated to include the effects of the flow over the whole car.

Use of Business Models within Model Driven Architecture

2009 ◽  
Vol 38 (38) ◽  
pp. 119-130
Author(s):  
Erika Asnina
Keyword(s):  
Business Models ◽  
Business Processes ◽  
Use Cases ◽  
Separation Of Concerns ◽  
Model Driven Architecture ◽  
Model Driven ◽  
Development Processes ◽  
Business Requirements ◽  
Complex Computer ◽  
Independent Model

Use of Business Models within Model Driven Architecture Model Driven Architecture is a framework dedicated for development of large and complex computer systems. It states and implements the principle of architectural separation of concerns. This means that a system can be modeled from three different but related to each other viewpoints. The viewpoint discussed in this paper is a Computation Independent one. MDA specification states that a model that shows a system from this viewpoint is a business model. Taking into account transformations foreseen by MDA, it should be useful for automation of software development processes. This paper discusses an essence of the Computation Independent Model (CIM) and the place of business models in the computation independent modeling. This paper considers four types of business models, namely, SBVR, BPMN, use cases and Topological Functioning Model (TFM). Business persons use SBVR to define business vocabularies and business rules of the existing and planned domains, BPMN to define business processes of both existing and planned domains, and use cases to define business requirements to the planned domain. The TFM is used to define functionality of both existing and planned domains. This paper discusses their capabilities to be used as complete CIMs with formally defined conformity between planned and existing domains.

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