dc.contributor.author | Pang, Wei | |
dc.contributor.author | Coghill, George M | |
dc.date.accessioned | 2014-12-09T10:03:01Z | |
dc.date.available | 2014-12-09T10:03:01Z | |
dc.date.issued | 2015-02 | |
dc.identifier | 43926660 | |
dc.identifier | 2a1c6a70-50e5-4fdf-b38c-9332c9e4c764 | |
dc.identifier | 84912553137 | |
dc.identifier.citation | Pang , 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.2014.11.008 | en |
dc.identifier.issn | 1568-4946 | |
dc.identifier.other | ORCID: /0000-0002-1761-6659/work/59923321 | |
dc.identifier.other | ORCID: /0000-0002-2047-8277/work/63561573 | |
dc.identifier.uri | http://hdl.handle.net/2164/4091 | |
dc.description | Acknowledgements 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.extent | 10 | |
dc.format.extent | 1521151 | |
dc.language.iso | eng | |
dc.relation.ispartof | Applied Soft Computing | en |
dc.subject | qualitative model learning | en |
dc.subject | artificial immune systems | en |
dc.subject | immune network approach | en |
dc.subject | compartmental models | en |
dc.subject | qualitative reasoning | en |
dc.subject | qualitative differential equation | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | Biotechnology and Biological Sciences Research Council (BBSRC) | en |
dc.subject | BB/F00513X/1 | en |
dc.subject.lcc | QA75 | en |
dc.title | QML-AiNet : an immune network approach to learning qualitative differential equation models | en |
dc.type | Journal article | en |
dc.contributor.institution | University of Aberdeen.Computing Science | en |
dc.description.status | Peer reviewed | en |
dc.identifier.doi | 10.1016/j.asoc.2014.11.008 | |