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dc.contributor.authorXiao, Fengen_US
dc.contributor.authorYuchi, Mingen_US
dc.contributor.authorDing, Mingyueen_US
dc.contributor.authorJo, Jun Hyungen_US
dc.contributor.editorIEEEen_US
dc.date.accessioned2017-05-16T12:30:43Z
dc.date.available2017-05-16T12:30:43Z
dc.date.issued2011en_US
dc.date.modified2012-05-28T22:15:41Z
dc.identifier.doi10.1109/ICBMI.2011.40en_US
dc.identifier.urihttp://hdl.handle.net/10072/45274
dc.description.abstractHeart rate (HR) signal analysis is widely used in the medicine and medical research area. Physical activities (PA) are commonly recognized to greatly affect the changes of heart rate. A method of Evolutionary Neural Network -- Neuroevolution of Augmenting Topologies (NEAT) is used to build a PA-based HR predictor model. Through special coding, crossover and mutation operator, NEAT can implement network topology and connectivity weights evolution simultaneously. The common problem in evolutionary neural network, like competing conventions, how to protect the new innovation are effectively solved. The experimental results demonstrated the application potential of the approach.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.publisherIEEEen_US
dc.publisher.placeUnited Statesen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofconferencenameInternational Conference on Intelligent Computation and Bio-Medical Instrumentation (ICBMI)en_US
dc.relation.ispartofconferencetitle2011 International Conference on Intelligent Computation and Bio-Medical Instrumentation (ICBMI)en_US
dc.relation.ispartofdatefrom2011-12-14en_US
dc.relation.ispartofdateto2011-12-17en_US
dc.relation.ispartoflocationWuhan, Chinaen_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchNeurosciences not elsewhere classifieden_US
dc.subject.fieldofresearchcode110999en_US
dc.titleA Research of Heart Rate Prediction Model Based on Evolutionary Neural Networken_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.date.issued2011
gro.hasfulltextNo Full Text


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