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UNICAMP - Ensemble based AHM and Optimization Flashcards | StudBud
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UNICAMP - Ensemble based AHM and Optimization
UNICAMP - Ensemble based AHM and Optimization
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1
Data Assimilation - Who was Kalman?
Mathematician
Statistician
Physicist
Engineer
2
Assisted History Matching - Defne the nature of the estimation in AHM
Parameter estimation
State and parameter estimation
State estimation
Observation estimation
3
Data Assimilaiton - What BLUE stands for?
Best Linear Under Estimation
Bayesian Linear Unbiased Estimator
A pop boys band
Best Linear Unbiased Estimator
4
Data Assimilation - What ES stands for?
Ensemble Smoother
Ensemble Setup
Errors statistics
Ensemble Simulation
5
Data Assimilation - What was Kalman's nationality?
Romanian
Hungarian
Croatian
Spanish
6
Data Assimialtion - In what bigger family of approaches this belongs?
Inverse modelling
Deterministic approach
Forward modelling
Data driven approach
7
Data Assimialtion - What assumption is not part of the Kalman Filter assumptions?
Linear model
Gaussian distributions
Nonlinear update
Model and observation error are independent
8
Data Assimilation - What is K (Kalman Gain) in case of a multivariable example
Observation covariance error
Weighting coefficient
Weighting matrix
Model covariance error
9
Bayes Theorem - Who was Bayes?
Physicist
Mathematician
Priest
Engineer
10
What P(B|A) represents?
Likelihood
Posteriori probability
Ensemble statistic
Prior probability
11
Data Assimilation - What is the "main engine" of the Ensemble Kalman Filter
Minimize the variance of the prior ensemble
Minimize the variance of observations
Minimize the diference between predicted observations and measured data
Maximize value
12
Data Assimialtion - When was the first paper published on EnKF and who's the author?
1996, Geir Evensen
1996, Geir Nævdal
1994, Geir Evensen
1994, Geir Nævdal