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dc.contributor.authorPang, Wei
dc.contributor.authorCoghill, George M
dc.date.accessioned2014-12-09T10:03:01Z
dc.date.available2014-12-09T10:03:01Z
dc.date.issued2015-02
dc.identifier43926660
dc.identifier2a1c6a70-50e5-4fdf-b38c-9332c9e4c764
dc.identifier84912553137
dc.identifier.citationPang , W & Coghill , G M 2015 , ' QML-AiNet : an immune network approach to learning qualitative differential equation models ' , Applied Soft Computing , vol. 27 , pp. 148-157 . https://doi.org/10.1016/j.asoc.2014.11.008en
dc.identifier.issn1568-4946
dc.identifier.otherORCID: /0000-0002-1761-6659/work/59923321
dc.identifier.otherORCID: /0000-0002-2047-8277/work/63561573
dc.identifier.urihttp://hdl.handle.net/2164/4091
dc.descriptionAcknowledgements WP and GMC are supported by the CRISP project (Combinatorial Responses in Stress Pathways) funded by the BBSRC (award reference: BB/F00513X/1) under the Systems Approaches to Biological Research (SABR) Initiative.en
dc.format.extent10
dc.format.extent1521151
dc.language.isoeng
dc.relation.ispartofApplied Soft Computingen
dc.subjectqualitative model learningen
dc.subjectartificial immune systemsen
dc.subjectimmune network approachen
dc.subjectcompartmental modelsen
dc.subjectqualitative reasoningen
dc.subjectqualitative differential equationen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectBiotechnology and Biological Sciences Research Council (BBSRC)en
dc.subjectBB/F00513X/1en
dc.subject.lccQA75en
dc.titleQML-AiNet : an immune network approach to learning qualitative differential equation modelsen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.description.statusPeer revieweden
dc.identifier.doi10.1016/j.asoc.2014.11.008


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