A core Course on Modeling Introduction to Modeling 0LAB0 0LBB0 0LCB0 0LDB0 S.29.

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A core Course on Modeling Introduction to Modeling 0LAB0 0LBB0 0LCB0 0LDB0 S.29

Execution: obtain result; Reflection: interpret result Right problem? (problem validation) Right concepts? (concepts validation) Right model? (model verification) Right outcome? (outcome verification) Right answer? (answer verification)

Glass box models compute values for output quantities in dependency of input quantities. For every purpose, defined in terms of output quantities, fulfilling the purpose means that the uncertainty distribution on the output quantities should be sufficiently small. So we should know this uncertainty to know if the model result is OK. Confidence for glass box models

1: examine dependencies in the functional network Confidence for glass box models ( structural confidence )

output input output input calculated expected 1: examine dependencies in the functional network select any pair of quantities, and graphically compare their dependency with what you expect,... Confidence for glass box models ( structural confidence )

output input output input calculated expected 1: examine dependencies in the functional network select any pair of quantities, and graphically compare their dependency with what you expect,... Confidence for glass box models ( structural confidence )

output input output input calculated expected 1: examine dependencies in the functional network select any pair of quantities, and graphically compare their dependency with what you expect,... Confidence for glass box models ( structural confidence )

output input output input calculated expected 1: examine dependencies in the functional network... in particular if they involve multiple parallel routes... Confidence for glass box models ( structural confidence )

output input output input calculated expected 1: examine dependencies in the functional network... in particular if they involve multiple parallel routes... Confidence for glass box models ( structural confidence )

output input output input calculated expected 1: examine dependencies in the functional network... in particular if they involve multiple parallel routes... Confidence for glass box models ( structural confidence )

output input output input calculated? expected? 1: examine dependencies in the functional network... and if there is no dependency, there is no graph. Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct 3: examine if singular behavior is correct Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct 3: examine if singular behavior is correct Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct 3: examine if singular behavior is correct Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct 3: examine if singular behavior is correct 4: examine if things that should converge have converged Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct 3: examine if singular behavior is correct 4: examine if things that should converge have converged Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct 3: examine if singular behavior is correct 4: examine if things that should converge have converged Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct 3: examine if singular behavior is correct 4: examine if things that should converge have converged Confidence for glass box models ( structural confidence )

1: examine dependencies in the functional network 2: examine if the long range behavior is correct 3: examine if singular behavior is correct 4: examine if things that should converge have converged validation verification validation validation Confidence for glass box models ( structural confidence )