System identification of nonlinear autoregressive models in monitoring dengue infection
This paper proposes system identification on application of nonlinear AR (NAR) based on Artificial Neural Network (ANN) for monitor of dengue infections. In building the model, three selection criteria, i.e. the final prediction error (FPE), Akaike's Information Criteria (AIC), and Lipschitz nu...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
2010
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/9348/1/System_identification_of_nonlinear_autoregressive_models_in_monitoring_dengue_infection.pdf http://eprints.um.edu.my/9348/ http://www.scopus.com/inward/record.url?eid=2-s2.0-79551508977&partnerID=40&md5=0491420521e068f90b645b6f6da2cc77 www-ist.massey.ac.nz/s2is/Issues/v3/n4/papers/paper13.pdf www.s2is.org/Issues/v3/n4/papers/paper13.pdf |
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http://eprints.um.edu.my/9348/1/System_identification_of_nonlinear_autoregressive_models_in_monitoring_dengue_infection.pdfhttp://eprints.um.edu.my/9348/
http://www.scopus.com/inward/record.url?eid=2-s2.0-79551508977&partnerID=40&md5=0491420521e068f90b645b6f6da2cc77 www-ist.massey.ac.nz/s2is/Issues/v3/n4/papers/paper13.pdf www.s2is.org/Issues/v3/n4/papers/paper13.pdf