Discriminant temporal patterns for linking physico-chemistry and biology in hydro-ecosystem assessment

Abstract : We propose a new data mining process to extract original knowledge from hydro-ecological data, in order to help the identification of pollution sources. This approach is based (1) on a domain knowledge discretization (quality classes) of physico-chemical and biological parameters, and (2) on an extraction of temporal patterns used as discriminant features to link physico-chemistry with biology in river sampling sites. For each bio-index quality value, we obtained a set of significant discriminant features. We used them to identify the physico-chemical characteristics that impact on different biological dimensions according to their presence in extracted knowledge. The experiments meet with the domain knowledge and also highlight significant mismatches between physico-chemical and biological quality classes. Then, we discuss about the interest of using discriminant temporal patterns for the exploration and the analysis of temporal environmental data such as hydro-ecological databases.
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Article dans une revue
Ecological Informatics, Elsevier, 2014, 24, pp.210-221. 〈10.1016/j.ecoinf.2014.09.003〉
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https://hal.archives-ouvertes.fr/hal-01090331
Contributeur : Florence Le Ber <>
Soumis le : mercredi 3 décembre 2014 - 13:27:32
Dernière modification le : mercredi 10 octobre 2018 - 14:28:11

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Mickaël Fabrègue, Agnès Braud, Sandra Bringay, Corinne Grac, Florence Le Ber, et al.. Discriminant temporal patterns for linking physico-chemistry and biology in hydro-ecosystem assessment. Ecological Informatics, Elsevier, 2014, 24, pp.210-221. 〈10.1016/j.ecoinf.2014.09.003〉. 〈hal-01090331〉

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