EQML- An Evolutionary Qualitative Model Learning Framework

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

7 Downloads (Pure)


In this paper, an Evolutionary Qualitative Model Learning Framework (EQML) is proposed and tested by learning the qualitative metabolic models under the condition of incomplete knowledge. JMorven, a fuzzy qualitative reasoning engine, is slightly modified and integrated into the framework as a sub module to represent and verify the learnt models. Three metabolic compartment models are tested by two evolutionary algorithms (Genetic Algorithm and Clonal Selection Algorithm) in EQML. Finally the efficiency of these two algorithms is evaluated.
Original languageEnglish
Title of host publication2nd European Symposium on Nature-inspired Smart Information Systems
Place of PublicationPuerto de la Cruz, Tenerife, Spain
Number of pages7
Publication statusPublished - 2006


Dive into the research topics of 'EQML- An Evolutionary Qualitative Model Learning Framework'. Together they form a unique fingerprint.

Cite this