PSO-Optimized CoVID-19 MLP-NARX Mortality Prediction Model
Mortality prediction models localized for Malaysia is limited, warranting a research gap to study further. A predictive model for CoVID-19 mortality prediction is presented in this paper. The model utilized the MLP-NARX structure. Parameters for the model were optimized using PSO. Prediction results...
| Published in: | IEACon 2021 - 2021 IEEE Industrial Electronics and Applications Conference |
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| Format: | Conference paper |
| Language: | English |
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Institute of Electrical and Electronics Engineers Inc.
2021
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124515858&doi=10.1109%2fIEACon51066.2021.9654684&partnerID=40&md5=314e6fd200c351feba040ca9433a5d07 |
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2-s2.0-85124515858 Yassin I.M.; Zabidi A.; Ali M.S.A.M.; Baharom R. PSO-Optimized CoVID-19 MLP-NARX Mortality Prediction Model 2021 IEACon 2021 - 2021 IEEE Industrial Electronics and Applications Conference 10.1109/IEACon51066.2021.9654684 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124515858&doi=10.1109%2fIEACon51066.2021.9654684&partnerID=40&md5=314e6fd200c351feba040ca9433a5d07 Mortality prediction models localized for Malaysia is limited, warranting a research gap to study further. A predictive model for CoVID-19 mortality prediction is presented in this paper. The model utilized the MLP-NARX structure. Parameters for the model were optimized using PSO. Prediction results yielded average MSE value of 8.1141× 10× {-7} with acceptable validation results. © 2021 IEEE. Institute of Electrical and Electronics Engineers Inc. English Conference paper |
| author |
Yassin I.M.; Zabidi A.; Ali M.S.A.M.; Baharom R. |
| spellingShingle |
Yassin I.M.; Zabidi A.; Ali M.S.A.M.; Baharom R. PSO-Optimized CoVID-19 MLP-NARX Mortality Prediction Model |
| author_facet |
Yassin I.M.; Zabidi A.; Ali M.S.A.M.; Baharom R. |
| author_sort |
Yassin I.M.; Zabidi A.; Ali M.S.A.M.; Baharom R. |
| title |
PSO-Optimized CoVID-19 MLP-NARX Mortality Prediction Model |
| title_short |
PSO-Optimized CoVID-19 MLP-NARX Mortality Prediction Model |
| title_full |
PSO-Optimized CoVID-19 MLP-NARX Mortality Prediction Model |
| title_fullStr |
PSO-Optimized CoVID-19 MLP-NARX Mortality Prediction Model |
| title_full_unstemmed |
PSO-Optimized CoVID-19 MLP-NARX Mortality Prediction Model |
| title_sort |
PSO-Optimized CoVID-19 MLP-NARX Mortality Prediction Model |
| publishDate |
2021 |
| container_title |
IEACon 2021 - 2021 IEEE Industrial Electronics and Applications Conference |
| container_volume |
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| container_issue |
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| doi_str_mv |
10.1109/IEACon51066.2021.9654684 |
| url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124515858&doi=10.1109%2fIEACon51066.2021.9654684&partnerID=40&md5=314e6fd200c351feba040ca9433a5d07 |
| description |
Mortality prediction models localized for Malaysia is limited, warranting a research gap to study further. A predictive model for CoVID-19 mortality prediction is presented in this paper. The model utilized the MLP-NARX structure. Parameters for the model were optimized using PSO. Prediction results yielded average MSE value of 8.1141× 10× {-7} with acceptable validation results. © 2021 IEEE. |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| issn |
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| language |
English |
| format |
Conference paper |
| accesstype |
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| record_format |
scopus |
| collection |
Scopus |
| _version_ |
1809677895005634560 |