Building complex models from available data is a challenge in many domains, and in particular in food science. Numerical data are often not enough structured, or simply not enough to elucidate complex structures: human choices have thus a major impact at various levels. LIDeOGraM is an interactive modelling framework adapted to cases where numerical data and expert knowledge have to be combined for building an efficient model. Exploiting both stand-alone evolutionary search and visual interaction with the user, the proposed methodology aims at obtaining an accurate global model for the system, balancing expert knowledge with information automatically extracted from available data. The presented framework is tested on a real-world case study from food science: the production and stabilisation of lactic acid bacteria, which has several important practical applications, ranging from assessing the efficacy of new industrial methods, to proposing alternative sustainable systems of food production.
CITATION STYLE
Chabin, T., Barnabé, M., Boukhelifa, N., Fonseca, F., Tonda, A., Velly, H., … Lutton, E. (2018). LIDeOGraM: An interactive evolutionary modelling tool. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10764 LNCS, pp. 189–201). Springer Verlag. https://doi.org/10.1007/978-3-319-78133-4_14
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