- author = "Olivier Barriere and Evelyne Lutton and Cedric Baudrit and Mariette Sicard and Bruno Pinaud and Nathalie Perrot",
- title = "Modeling human expertise on a cheese ripening industrial process using GP",
- booktitle = "Parallel Problem Solving from Nature - PPSN X",
- year = "2008",
- editor = "Gunter Rudolph and Thomas Jansen and Simon Lucas and Carlo Poloni and Nicola Beume",
- volume = "5199",
- series = "LNCS",
- pages = "859--868",
- address = "Dortmund",
- month = "13-17 " # sep,
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "3-540-87699-5",
-
url_fake = "
http://metronum.futurs.inria.fr/html/Papers/files/pdf/Barriere_18-06-2008_INCALIN-PPSN2008-Final.pdf",
-
DOI = "
doi:10.1007/978-3-540-87700-4_85",
- size = "10 pages",
- abstract = "Industrial agrifood processes often strongly rely on human expertise, expressed as know-how and control procedures based on subjective measurements (colour, smell, texture), which are very difficult to capture and model. We deal in this paper with a cheese ripening process (of French Camembert), for which experimental data have been collected within a cheese ripening laboratory chain. A global and a monopopulation cooperative/coevolutive GP scheme (Parisian approach) have been developed in order to simulate phase prediction (i.e. a subjective estimation of human experts) from microbial proportions and Ph measurements. These two GP approaches are compared to Bayesian network modelling and simple multilinear learning algorithms. Preliminary results show the effectiveness and robustness of the Parisian GP approach.",
-
notes = "GPLAB, Matlab, multi linear regression, INCALIN,
Terminals: time derivatives of pH acidity, lactose and
two bacteria concentrations. Gaussian random constants.
Function set: arithmetics, log, exp?, Boolean ops.
Fitness: parsimony, Euclidean sharing distance. tree
GP. 30-40 nodes. Mutation Chi squared. 16 experiments
each lasting 40 days. Missing data estimated by fitting
splines. Log? distribution on floats. See also
\cite{inria-00381681}
PPSN X",
