Combining Grammatical Evolution with Modal Interval Analysis: An Application to Solve Problems with Uncertainty
dc.contributor.author
dc.date.accessioned
2021-04-06T14:11:07Z
dc.date.available
2021-04-06T14:11:07Z
dc.date.issued
2021-03-16
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2227-7390
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dc.description.abstract
Complex systems are usually affected by various sources of uncertainty, and it is essential to account for mechanisms that ensure the proper management of such disturbances. This paper introduces a novel approach to solve symbolic regression problems, which combines the potential of Grammatical Evolution to obtain solutions by describing the search space with context-free grammars, and the ability of Modal Interval Analysis (MIA) to handle quantified uncertainty. The presented methodology uses an MIA solver to evaluate the fitness function, which represents a novel method to manage uncertainty by means of interval-based prediction models. This paper first introduces the theory that establishes the basis of the proposed methodology, and follows with a description of the system architecture and implementation details. Then, we present an illustrative application example which consists of determining the outer and inner approximations of the mean velocity of the water current of a river stretch. Finally, the interpretation of the obtained results and the limitations of the proposed methodology are discussed
dc.description.sponsorship
This work was partially supported by the Spanish Ministry of Science and Innovation through grant PID2019-107722RB-C22/AEI/10.13039/501100011033 and the Government of Catalonia under 2017SGR1551
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application/pdf
dc.language.iso
eng
dc.publisher
MDPI (Multidisciplinary Digital Publishing Institute)
dc.relation
PID2019-107722RB-C22
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Reproducció digital del document publicat a: https://doi.org/10.3390/math9060631
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Mathematics, 2021, vol. 9, núm.6, p. 631
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Articles publicats (D-EEEiA)
dc.rights
Attribution 4.0 International
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dc.subject
dc.title
Combining Grammatical Evolution with Modal Interval Analysis: An Application to Solve Problems with Uncertainty
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.relation.projectID
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107722RB-C22/ES/PATIENT-TAILORED SOLUTIONS FOR BLOOD GLUCOSE CONTROL IN TYPE 1 DIABETES/
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.contributor.funder
dc.type.peerreviewed
peer-reviewed
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