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dc.contributor.authorvon Grabe, J
dc.contributor.authorKorsavi, S
dc.date.accessioned2022-02-12T16:41:09Z
dc.date.available2022-02-12T16:41:09Z
dc.date.issued2022-02-04
dc.identifier.issn2517-7567
dc.identifier.issn2517-7567
dc.identifier.urihttp://hdl.handle.net/10026.1/18758
dc.description.abstract

Energy consumption in buildings is a major contributor to global warming and therefore has become a field of intensive research. This type of energy consumption can be described in two dimensions: an appliance-based dimension and a behaviour-based dimension. To address the behaviour-based dimension a recent study proposed a cognitive human-building interaction model that builds on the instance-based learning paradigm. However, since the values of the standard cognitive parameters commonly used for modelling lab-based behaviours are not suitable for the ‘real-world’ domain of human-building interaction, this paper aims to identify cognitive parameter values adapted to and suitable for the specific character of this application domain. To achieve this goal, a virtual test environment—consisting of an occupied room and a corresponding model task—was designed to test the performance of the model and its dependence on a set of fundamental cognitive parameters. A test criterion was developed that did not depend on empirical data but used the predictive consistency of the model as reference. A range of values was pre-selected for each parameter based on theoretical and empirical considerations, which was then tested against the evaluation criterion. The performance of the model was improved significantly throughout the parametrisation process and yielded plausible results.

dc.format.extent45-67
dc.languageen
dc.language.isoen
dc.publisherWiley Open Access
dc.rightsAttribution 4.0 International
dc.rightsAttribution 4.0 International
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject46 Information and Computing Sciences
dc.subject3301 Architecture
dc.subject33 Built Environment and Design
dc.subjectMind and Body
dc.titleA psychological model for the prediction of energy‐relevant behaviours in buildings: Cognitive parameter optimisation
dc.typejournal-article
dc.typeJournal Article
plymouth.issue1
plymouth.volume4
plymouth.publisher-urlhttp://dx.doi.org/10.1049/ccs2.12042
plymouth.publication-statusPublished
plymouth.journalCognitive Computation and Systems
dc.identifier.doi10.1049/ccs2.12042
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Arts, Humanities and Business
plymouth.organisational-group/Plymouth/Faculty of Arts, Humanities and Business/School of Art, Design and Architecture
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dcterms.dateAccepted2021-12-03
dc.rights.embargodate2022-2-15
dc.identifier.eissn2517-7567
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1049/ccs2.12042
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
rioxxterms.licenseref.startdate2022-02-04
rioxxterms.typeJournal Article/Review


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