%0 Conference Paper %1 Freyeretal1998 %A Freyer, Stephan %A Graefe, Jörg %A Heinzel, Matthias %A Marenbach, Peter %B Eufit '98, 6th European Congress on Intelligent Techniques and Soft Computing, ELITE - European Laboratory for Intelligent TechniquesEngineering %C Aachen, Germany %D 1998 %E Zimmermann, Hans-Jürgen %K SMOG, algorithms, bioprocess, genetic modelling programming, %P 1471--1475 %T Evolutionary Generation and Refinement of Mathematical Process Models %U http://www.rt.e-technik.tu-darmstadt.de/LIT %V III %X Modelling of biotechnological processes is generally difficult and time consuming. In order to generate mathematical models of a studied reaction system in a short time period a new modelling technique for the optimisation of structures, based on the principles of evolution, was developed. This method generates transparent and comprehensible dynamic models in a data driven manner. In addition it is able to automatically refine sub-models or to verify model ideas. The transparent mathematical form of the generated models is a major advantage giving the user the opportunity to interpret the model and to influence the modelling process interactively. The article at hand presents two examples of biotechnological processes for which this new method was successfully applied.

@inproceedings{Freyeretal1998, abstract = {Modelling of biotechnological processes is generally difficult and time consuming. In order to generate mathematical models of a studied reaction system in a short time period a new modelling technique for the optimisation of structures, based on the principles of evolution, was developed. This method generates transparent and comprehensible dynamic models in a data driven manner. In addition it is able to automatically refine sub-models or to verify model ideas. The transparent mathematical form of the generated models is a major advantage giving the user the opportunity to interpret the model and to influence the modelling process interactively. The article at hand presents two examples of biotechnological processes for which this new method was successfully applied.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Aachen, Germany}, author = {Freyer, Stephan and Graefe, J{\"o}rg and Heinzel, Matthias and Marenbach, Peter}, biburl = {https://www.bibsonomy.org/bibtex/2d896dd0212cccd6ae9c05e2691452f02/brazovayeye}, booktitle = {Eufit '98, 6th European Congress on Intelligent Techniques and Soft Computing, ELITE - European Laboratory for Intelligent TechniquesEngineering}, editor = {Zimmermann, Hans-J{\"u}rgen}, email = {pmarenbach@gmx.net}, interhash = {89fbaeb94a241c4e32ca3bf4eb7e5dd9}, intrahash = {d896dd0212cccd6ae9c05e2691452f02}, keywords = {SMOG, algorithms, bioprocess, genetic modelling programming,}, notes = {http://www.eufit.org/proceedings/98/volume3.htm BASF AG laboratories, high noise. Monod, SubLimTeissier, SubLimJost, SubInhAnstrews, SubInhWebb MATLAB/SIMULINK. Stresses importance of user understandable models, using prior knowledge, parsimony versus accuracy (trade off in fitness function). Batch fed fermentation.}, pages = {1471--1475}, size = {5 page}, timestamp = {2008-06-19T17:39:51.000+0200}, title = {Evolutionary Generation and Refinement of Mathematical Process Models}, url = {http://www.rt.e-technik.tu-darmstadt.de/LIT}, volume = {III}, year = 1998 }