An intelligent risk assessment on prediction of COVID-19 pandemic using DNN and TSA: An empirical case study in Thailand
The WHO has declared that the COVID-19 pandemic is a severe health crisis. Currently, variants of concern are delta and omicron, including sub-lineages of the omicron which are XBB and BQ.1 variants. Decision planning with situation awareness is important during the COVID-19 pandemic, especially dem...
Saved in:
| Published in: | Expert systems with applications Vol. 253; p. 124311 |
|---|---|
| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01.11.2024
|
| Subjects: | |
| ISSN: | 0957-4174, 1873-6793 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | The WHO has declared that the COVID-19 pandemic is a severe health crisis. Currently, variants of concern are delta and omicron, including sub-lineages of the omicron which are XBB and BQ.1 variants. Decision planning with situation awareness is important during the COVID-19 pandemic, especially demand planning for medical supplies following pandemic probability or severity via pandemic risk assessment. Therefore, this research proposes an intelligent risk assessment on the prediction of the COVID-19 pandemic using deep learning with deep neural network (DNN) and tunicate swarm algorithm (TSA). The results show the model can accurately predict the distance and elapsed time of the next COVID-19 case based upon the previous case and evaluate the associated risks. The contribution of this research, as prediction model is based upon a DNN, it has the ability to learn and by implementing the TSA, it can improve theoretically the performance of the DNN for more precise prediction and faster convergence to the optimal solution. The prediction results are practically expanded to analyze risk assessment using probability and the data envelopment analysis (DEA). The benefit of this research is that the proposed methodology demonstrates the prediction results using risks assessment based upon intelligent risk assessment charts. The Government or those involved can use the proposed methodology to achieve a better decision-making and management to control the COVID-19 pandemic in terms of supplying the medical supplies into pandemic areas. |
|---|---|
| AbstractList | The WHO has declared that the COVID-19 pandemic is a severe health crisis. Currently, variants of concern are delta and omicron, including sub-lineages of the omicron which are XBB and BQ.1 variants. Decision planning with situation awareness is important during the COVID-19 pandemic, especially demand planning for medical supplies following pandemic probability or severity via pandemic risk assessment. Therefore, this research proposes an intelligent risk assessment on the prediction of the COVID-19 pandemic using deep learning with deep neural network (DNN) and tunicate swarm algorithm (TSA). The results show the model can accurately predict the distance and elapsed time of the next COVID-19 case based upon the previous case and evaluate the associated risks. The contribution of this research, as prediction model is based upon a DNN, it has the ability to learn and by implementing the TSA, it can improve theoretically the performance of the DNN for more precise prediction and faster convergence to the optimal solution. The prediction results are practically expanded to analyze risk assessment using probability and the data envelopment analysis (DEA). The benefit of this research is that the proposed methodology demonstrates the prediction results using risks assessment based upon intelligent risk assessment charts. The Government or those involved can use the proposed methodology to achieve a better decision-making and management to control the COVID-19 pandemic in terms of supplying the medical supplies into pandemic areas. |
| ArticleNumber | 124311 |
| Author | Kengpol, Athakorn Klunngien, Jakkarin |
| Author_xml | – sequence: 1 givenname: Athakorn orcidid: 0000-0002-2637-601X surname: Kengpol fullname: Kengpol, Athakorn email: athakorn@kmutnb.ac.th organization: Advanced Industrial Engineering Management Systems Research Center, Department of Industrial Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand – sequence: 2 givenname: Jakkarin orcidid: 0000-0003-2238-1329 surname: Klunngien fullname: Klunngien, Jakkarin email: sfengjkk@src.ku.ac.th organization: Industrial and Production Management Research Unit, Department of Industrial Engineering, Faculty of Engineering at Sriracha, Kasetsart University, Sriracha, Thailand |
| BookMark | eNp9kN1OwjAUgBuDiYC-gFd9gc123ehmvCHgDwmBC9HbpmvPsLh1pB0qb28XvPKCq_OT8532fCM0sK0FhG4piSmhk7tdDP5bxglJ0pgmKaP0Ag1pzlk04QUboCEpMh6llKdXaOT9jhDKCeFD9DO12NgO6tpswXbYGf-JpffgfdPXrcV7B9qozoS0rfBs_b6YR7TAe2k1NEbhgzd2i-erFQ4dvHmd3uOwFJq9cUbJGivpAfvuoI_hJbz5kKYOg9fospK1h5u_OEZvT4-b2Uu0XD8vZtNlpBghXUS5zpOCQKYKlZcVV1mmNXClacppKUmipZJFlUOeZmVBaTkp80mRMEYYY6VmbIyS017lWu8dVGLvTCPdUVAiendiJ3p3oncnTu4ClP-DlOlkr6Bz4fvn0YcTCuGoLwNOeGXAquDQgeqEbs05_BegPYxQ |
| CitedBy_id | crossref_primary_10_1007_s10489_025_06802_w crossref_primary_10_1007_s11831_025_10228_5 crossref_primary_10_1016_j_autcon_2024_105648 crossref_primary_10_3390_app15137373 |
| Cites_doi | 10.1007/s00521-022-07424-w 10.1016/j.eswa.2019.06.039 10.1016/j.measurement.2020.108843 10.32604/cmc.2020.012441 10.1016/j.gsf.2020.09.006 10.1016/j.ijpe.2018.11.024 10.1016/j.conbuildmat.2017.11.006 10.1016/S2213-2600(20)30121-1 10.1504/IJISE.2022.126984 10.1016/j.jairtraman.2019.101707 10.1007/s12553-022-00722-2 10.1016/j.jlp.2018.08.018 10.1016/j.engappai.2020.103541 10.1016/j.amjmed.2021.01.020 10.1016/j.agwat.2020.106547 10.3390/technologies9040081 10.1016/j.isatra.2021.02.016 10.1108/EC-03-2017-0105 10.1016/j.jafr.2021.100154 10.1016/j.cie.2019.04.041 10.1016/j.ijtst.2020.03.004 10.3389/fmicb.2019.02752 10.1016/j.jhin.2020.05.027 10.1016/j.promfg.2020.01.226 10.1016/j.jenvman.2021.113085 10.1016/0377-2217(78)90138-8 10.1016/j.eswa.2021.115190 10.1016/j.tust.2021.103951 10.1007/s00521-020-05104-1 10.1016/j.asej.2021.06.009 10.1007/s00521-021-06346-3 10.1007/s12553-022-00691-6 10.1016/j.cie.2014.06.003 10.1016/j.jclepro.2020.121672 10.1016/j.jmapro.2018.04.015 10.1080/00207543.2015.1041570 10.1213/ANE.0000000000005063 10.1016/j.ijpe.2020.107921 10.1007/s10845-020-01538-5 |
| ContentType | Journal Article |
| Copyright | 2024 Elsevier Ltd |
| Copyright_xml | – notice: 2024 Elsevier Ltd |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.eswa.2024.124311 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1873-6793 |
| ExternalDocumentID | 10_1016_j_eswa_2024_124311 S0957417424011771 |
| GroupedDBID | --K --M .DC .~1 0R~ 13V 1B1 1RT 1~. 1~5 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN 9JO AAAKF AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AARIN AAXUO AAYFN ABBOA ABFNM ABMAC ABMVD ABUCO ACDAQ ACGFS ACHRH ACNTT ACRLP ACZNC ADBBV ADEZE ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGUMN AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJOXV AKRWK ALEQD ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD APLSM AXJTR BJAXD BKOJK BLXMC BNSAS CS3 DU5 EBS EFJIC EO8 EO9 EP2 EP3 F5P FDB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HAMUX IHE J1W JJJVA KOM MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. PQQKQ Q38 RIG ROL RPZ SDF SDG SDP SDS SES SEW SPC SPCBC SSB SSD SSL SST SSV SSZ T5K TN5 ~G- 29G 9DU AAAKG AAQXK AATTM AAXKI AAYWO AAYXX ABJNI ABKBG ABUFD ABWVN ABXDB ACLOT ACNNM ACRPL ACVFH ADCNI ADJOM ADMUD ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKYEP ANKPU APXCP ASPBG AVWKF AZFZN CITATION EFKBS EFLBG EJD FEDTE FGOYB G-2 HLZ HVGLF HZ~ LG9 LY1 LY7 M41 R2- SBC SET WUQ XPP ZMT ~HD |
| ID | FETCH-LOGICAL-c300t-17d8290e5c9c8bf7c55dde7cd1471ba02daca9f8e845b911b6b8692330333bd33 |
| ISICitedReferencesCount | 5 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001247382700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0957-4174 |
| IngestDate | Sat Nov 29 03:07:38 EST 2025 Tue Nov 18 22:12:49 EST 2025 Tue Jun 18 08:50:57 EDT 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Tunicate swarm algorithm Deep neural network Prediction of COVID-19 pandemic Risk assessment Data envelopment analysis |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c300t-17d8290e5c9c8bf7c55dde7cd1471ba02daca9f8e845b911b6b8692330333bd33 |
| ORCID | 0000-0003-2238-1329 0000-0002-2637-601X |
| ParticipantIDs | crossref_primary_10_1016_j_eswa_2024_124311 crossref_citationtrail_10_1016_j_eswa_2024_124311 elsevier_sciencedirect_doi_10_1016_j_eswa_2024_124311 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-11-01 2024-11-00 |
| PublicationDateYYYYMMDD | 2024-11-01 |
| PublicationDate_xml | – month: 11 year: 2024 text: 2024-11-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationTitle | Expert systems with applications |
| PublicationYear | 2024 |
| Publisher | Elsevier Ltd |
| Publisher_xml | – name: Elsevier Ltd |
| References | Nhu Nguyen, Ho Le Viet, Prasad Joshi, Shrestha (b0115) 2020; 66 Ramanathan, Antognini, Combes, Paden, Zakhary, Ogino, MacLaren, Brodie, Shekar (b0150) 2020; 8 Iyer, Jain (b0060) 2019; 81 Yang, Lin, Gu, Liang (b0205) 2018; 35 Peykani, Mohammadi, Emrouznejad, Pishvaee, Rostamy-Malkhalifeh (b0125) 2019; 136 Singh, Gupta (b0160) 2022; 124 Kengpol, Tuammee (b0085) 2015; 54 Kengpol, Klunngien (b0070) 2019; 39 World Health Organization. (2022, 26 October 2022). COVID-19 Weekly Epidemiological Update. Kwok, Chan, Huang, Hui, Tambyah, Wei, Chau, Wong, Tang (b0090) 2020; 105 Mahajan, Caraballo, Li, Dong, Chen, Huston, Srinivasan, Redlich, Ko, Faust, Forman, Krumholz (b0100) 2021; 134 Pan, Wang, Zhou, Yan, Guo (b0120) 2020; 31 Qi, Fourie, Chen (b0130) 2018; 159 Ivanov, Dolgui (b0055) 2021; 232 Araz, Olson, Ramirez-Nafarrate (b0010) 2019; 208 da Silva, Francisquini, Nascimento (b0020) 2021; 182 Radanliev, De Roure (b0140) 2022; 12 Xiao, Hu, Li (b0195) 2021; 171 Hou, Zhuang, Tang, He, Miao, Huang, Luo (b0050) 2021; 5 Vörösmarty, Dobos (b0180) 2020; 264 Latif, Birima, Ahmed, Hatem, Al-Ansari, Fai, El-Shafie (b0095) 2022; 13 Akolaş, Kaleli, Bakirci (b0005) 2020; 33 Charnes, Cooper, Rhodes (b0015) 1978; 2 Valdenebro, Gimena, López (b0175) 2021; 113 Tsui, Deng, Pan (b0170) 2020; 131 Melek (b0110) 2021; 33 Radanliev, De Roure (b0145) 2023; 13 Department of Disease Control. (2022). Corona Virus Disease (COVID-19) in Thailand Situation . Fan, Zheng, Wu, Zhang (b0030) 2021; 245 Kengpol, Klunngien (b0075) 2022; 42 Guo, Wei, Zhang, Wu, Li, Zhou, Qu (b0035) 2019; 10 Markoulidakis, Rallis, Georgoulas, Kopsiaftis, Doulamis, Doulamis (b0105) 2021; 9 Heidari, Jafari Navimipour, Unal, Toumaj (b0045) 2022; 34 Kengpol, Neungrit (b0080) 2014; 75 Hatami-Marbini, Toloo (b0040) 2019; 133 Kaur, Awasthi, Sangal, Dhiman (b0065) 2020; 90 Xu, Chen, Zhang (b0200) 2021; 295 Zhao, Liu, Liu, Zhang, Li (b0210) 2018; 56 Qiu, Zheng, Du, Jiang (b0135) 2020; 9 Sagai Francis Britto, Edwin Raj, Carolin Mabel (b0155) 2018; 32 World Health Organization. (2023). Information note on new COVID-19 Omicron subvariant XBB.1.5. Towfiqul Islam, Talukdar, Mahato, Kundu, Eibek, Pham, Kuriqi, Linh (b0165) 2021; 12 Kengpol (10.1016/j.eswa.2024.124311_b0075) 2022; 42 Latif (10.1016/j.eswa.2024.124311_b0095) 2022; 13 Kengpol (10.1016/j.eswa.2024.124311_b0080) 2014; 75 Guo (10.1016/j.eswa.2024.124311_b0035) 2019; 10 10.1016/j.eswa.2024.124311_b0190 Peykani (10.1016/j.eswa.2024.124311_b0125) 2019; 136 Qi (10.1016/j.eswa.2024.124311_b0130) 2018; 159 Valdenebro (10.1016/j.eswa.2024.124311_b0175) 2021; 113 Singh (10.1016/j.eswa.2024.124311_b0160) 2022; 124 Araz (10.1016/j.eswa.2024.124311_b0010) 2019; 208 Kengpol (10.1016/j.eswa.2024.124311_b0085) 2015; 54 Charnes (10.1016/j.eswa.2024.124311_b0015) 1978; 2 Hatami-Marbini (10.1016/j.eswa.2024.124311_b0040) 2019; 133 Kaur (10.1016/j.eswa.2024.124311_b0065) 2020; 90 da Silva (10.1016/j.eswa.2024.124311_b0020) 2021; 182 Heidari (10.1016/j.eswa.2024.124311_b0045) 2022; 34 Kengpol (10.1016/j.eswa.2024.124311_b0070) 2019; 39 Xiao (10.1016/j.eswa.2024.124311_b0195) 2021; 171 Yang (10.1016/j.eswa.2024.124311_b0205) 2018; 35 Xu (10.1016/j.eswa.2024.124311_b0200) 2021; 295 10.1016/j.eswa.2024.124311_b0185 10.1016/j.eswa.2024.124311_b0025 Vörösmarty (10.1016/j.eswa.2024.124311_b0180) 2020; 264 Zhao (10.1016/j.eswa.2024.124311_b0210) 2018; 56 Sagai Francis Britto (10.1016/j.eswa.2024.124311_b0155) 2018; 32 Ivanov (10.1016/j.eswa.2024.124311_b0055) 2021; 232 Hou (10.1016/j.eswa.2024.124311_b0050) 2021; 5 Radanliev (10.1016/j.eswa.2024.124311_b0145) 2023; 13 Ramanathan (10.1016/j.eswa.2024.124311_b0150) 2020; 8 Mahajan (10.1016/j.eswa.2024.124311_b0100) 2021; 134 Markoulidakis (10.1016/j.eswa.2024.124311_b0105) 2021; 9 Towfiqul Islam (10.1016/j.eswa.2024.124311_b0165) 2021; 12 Fan (10.1016/j.eswa.2024.124311_b0030) 2021; 245 Pan (10.1016/j.eswa.2024.124311_b0120) 2020; 31 Nhu Nguyen (10.1016/j.eswa.2024.124311_b0115) 2020; 66 Akolaş (10.1016/j.eswa.2024.124311_b0005) 2020; 33 Iyer (10.1016/j.eswa.2024.124311_b0060) 2019; 81 Melek (10.1016/j.eswa.2024.124311_b0110) 2021; 33 Radanliev (10.1016/j.eswa.2024.124311_b0140) 2022; 12 Kwok (10.1016/j.eswa.2024.124311_b0090) 2020; 105 Qiu (10.1016/j.eswa.2024.124311_b0135) 2020; 9 Tsui (10.1016/j.eswa.2024.124311_b0170) 2020; 131 |
| References_xml | – volume: 35 start-page: 1625 year: 2018 end-page: 1638 ident: b0205 article-title: Prediction and optimization model of activated carbon double layer capacitors based on improved heuristic approach genetic algorithm neural network publication-title: Engineering Computations – volume: 105 start-page: 682 year: 2020 end-page: 685 ident: b0090 article-title: Inferring super-spreading from transmission clusters of COVID-19 in Hong Kong, Japan, and Singapore publication-title: The Journal of Hospital Infection – volume: 81 year: 2019 ident: b0060 article-title: Performance measurement of airports using data envelopment analysis: A review of methods and findings publication-title: Journal of Air Transport Management – volume: 113 year: 2021 ident: b0175 article-title: The transformation of a trade fair and exhibition centre into a field hospital for COVID-19 patients via multi-utility tunnels publication-title: Tunnelling and Underground Space Technology – volume: 9 start-page: 322 year: 2020 end-page: 333 ident: b0135 article-title: Performance evaluation of transit signal priorities on bus transit corridor based on data envelopment analysis publication-title: International Journal of Transportation Science and Technology – volume: 171 year: 2021 ident: b0195 article-title: A model-based health indicator for leak detection in gas pipeline systems publication-title: Measurement – volume: 33 start-page: 17621 year: 2021 end-page: 17632 ident: b0110 article-title: Diagnosis of COVID-19 and non-COVID-19 patients by classifying only a single cough sound publication-title: Neural Computing and Applications – volume: 75 start-page: 55 year: 2014 end-page: 67 ident: b0080 article-title: A decision support methodology with risk assessment on prediction of terrorism insurgency distribution range radius and elapsing time: An empirical case study in Thailand publication-title: Computers & Industrial Engineering – volume: 33 start-page: 1655 year: 2020 end-page: 1670 ident: b0005 article-title: Design and implementation of an autonomous EGR cooling system using deep neural network prediction to reduce NOx emission and fuel consumption of diesel engine publication-title: Neural Computing and Applications – volume: 13 year: 2022 ident: b0095 article-title: Development of prediction model for phosphate in reservoir water system based machine learning algorithms publication-title: Ain Shams Engineering Journal – volume: 56 start-page: 95 year: 2018 end-page: 103 ident: b0210 article-title: A safety vulnerability assessment for chemical enterprises: A hybrid of a data envelopment analysis and fuzzy decision-making publication-title: Journal of Loss Prevention in the Process Industries – volume: 182 year: 2021 ident: b0020 article-title: Meteorological and human mobility data on predicting COVID-19 cases by a novel hybrid decomposition method with anomaly detection analysis: A case study in the capitals of Brazil publication-title: Expert Systems With Applications – volume: 133 start-page: 331 year: 2019 end-page: 338 ident: b0040 article-title: Data envelopment analysis models with ratio data: A revisit publication-title: Computers & Industrial Engineering – volume: 42 start-page: 319 year: 2022 end-page: 337 ident: b0075 article-title: Design of a machine learning to classify health beverages preferences for elderly people: An empirical study during COVID-19 in Thailand publication-title: International Journal of Industrial and Systems Engineering – volume: 9 year: 2021 ident: b0105 article-title: Multiclass confusion matrix reduction method and its application on net promoter score classification problem publication-title: Technologies – volume: 8 start-page: 518 year: 2020 end-page: 526 ident: b0150 article-title: Planning and provision of ECMO services for severe ARDS during the COVID-19 pandemic and other outbreaks of emerging infectious diseases publication-title: The Lancet Respiratory Medicine – volume: 124 start-page: 31 year: 2022 end-page: 40 ident: b0160 article-title: Generalized SIR (GSIR) epidemic model: An improved framework for the predictive monitoring of COVID-19 pandemic publication-title: ISA Transactions – volume: 264 year: 2020 ident: b0180 article-title: A literature review of sustainable supplier evaluation with Data Envelopment Analysis publication-title: Journal of Cleaner Production – volume: 54 start-page: 1020 year: 2015 end-page: 1038 ident: b0085 article-title: The development of a decision support framework for a quantitative risk assessment in multimodal green logistics: An empirical study publication-title: International Journal of Production Research – reference: World Health Organization. (2023). Information note on new COVID-19 Omicron subvariant XBB.1.5. – volume: 136 start-page: 439 year: 2019 end-page: 452 ident: b0125 article-title: Fuzzy data envelopment analysis: An adjustable approach publication-title: Expert Systems with Applications – reference: World Health Organization. (2022, 26 October 2022). COVID-19 Weekly Epidemiological Update. – volume: 208 start-page: 199 year: 2019 end-page: 207 ident: b0010 article-title: Predictive analytics for hospital admissions from the emergency department using triage information publication-title: International Journal of Production Economics – volume: 90 year: 2020 ident: b0065 article-title: Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization publication-title: Engineering Applications of Artificial Intelligence – volume: 13 start-page: 11 year: 2023 end-page: 15 ident: b0145 article-title: Disease X vaccine production and supply chains: Risk assessing healthcare systems operating with artificial intelligence and industry 4.0 publication-title: Health and Technology (Berl) – volume: 32 start-page: 828 year: 2018 end-page: 838 ident: b0155 article-title: Prediction and optimization of mechanical strength of diffusion bonds using integrated ANN-GA approach with process variables and metallographic characteristics publication-title: Journal of Manufacturing Processes – volume: 39 start-page: 40 year: 2019 end-page: 49 ident: b0070 article-title: The development of cyber-physical framework for classifying health beverage flavor for the ageing society publication-title: Procedia Manufacturing – volume: 2 start-page: 429 year: 1978 end-page: 444 ident: b0015 article-title: Measuring the efficiency of decision making units publication-title: European Journal of Operational Research – volume: 5 year: 2021 ident: b0050 article-title: Recognition of early blight and late blight diseases on potato leaves based on graph cut segmentation publication-title: Journal of Agriculture and Food Research – volume: 34 start-page: 15313 year: 2022 end-page: 15348 ident: b0045 article-title: Machine learning applications for COVID-19 outbreak management publication-title: Neural Computing and Applications – volume: 12 year: 2021 ident: b0165 article-title: Flood susceptibility modelling using advanced ensemble machine learning models publication-title: Geoscience Frontiers – volume: 66 start-page: 551 year: 2020 end-page: 562 ident: b0115 article-title: Intelligent tunicate swarm-optimization-algorithm-based lightweight security mechanism in internet of health things publication-title: Computers, Materials & Continua – volume: 245 year: 2021 ident: b0030 article-title: Estimation of daily maize transpiration using support vector machines, extreme gradient boosting, artificial and deep neural networks models publication-title: Agricultural Water Management – volume: 131 year: 2020 ident: b0170 article-title: COVID-19: Epidemiological factors during aerosol-generating medical procedures publication-title: Anesthesia & Analgesia – reference: . – volume: 10 start-page: 2752 year: 2019 ident: b0035 article-title: Clinical features predicting mortality risk in patients with viral pneumonia: The MuLBSTA score publication-title: Frontiers in Microbiology – volume: 232 year: 2021 ident: b0055 article-title: OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications publication-title: International Journal of Production Economics – volume: 159 start-page: 473 year: 2018 end-page: 478 ident: b0130 article-title: Neural network and particle swarm optimization for predicting the unconfined compressive strength of cemented paste backfill publication-title: Construction and Building Materials – volume: 295 year: 2021 ident: b0200 article-title: Predicting river dissolved oxygen time series based on stand-alone models and hybrid wavelet-based models publication-title: Journal of Environmental Management – reference: Department of Disease Control. (2022). Corona Virus Disease (COVID-19) in Thailand Situation – volume: 31 start-page: 1825 year: 2020 end-page: 1836 ident: b0120 article-title: Activation functions selection for BP neural network model of ground surface roughness publication-title: Journal of Intelligent Manufacturing – volume: 134 start-page: 812 year: 2021 end-page: 816 e812 ident: b0100 article-title: SARS-CoV-2 infection hospitalization rate and infection fatality rate among the non-congregate population in connecticut publication-title: The American Journal of Medicine – volume: 12 start-page: 923 year: 2022 end-page: 929 ident: b0140 article-title: Advancing the cybersecurity of the healthcare system with self-optimising and self-adaptative artificial intelligence (part 2) publication-title: Health and Technology (Berl) – volume: 34 start-page: 15313 issue: 18 year: 2022 ident: 10.1016/j.eswa.2024.124311_b0045 article-title: Machine learning applications for COVID-19 outbreak management publication-title: Neural Computing and Applications doi: 10.1007/s00521-022-07424-w – ident: 10.1016/j.eswa.2024.124311_b0190 – volume: 136 start-page: 439 year: 2019 ident: 10.1016/j.eswa.2024.124311_b0125 article-title: Fuzzy data envelopment analysis: An adjustable approach publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2019.06.039 – volume: 171 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0195 article-title: A model-based health indicator for leak detection in gas pipeline systems publication-title: Measurement doi: 10.1016/j.measurement.2020.108843 – ident: 10.1016/j.eswa.2024.124311_b0025 – volume: 66 start-page: 551 issue: 1 year: 2020 ident: 10.1016/j.eswa.2024.124311_b0115 article-title: Intelligent tunicate swarm-optimization-algorithm-based lightweight security mechanism in internet of health things publication-title: Computers, Materials & Continua doi: 10.32604/cmc.2020.012441 – volume: 12 issue: 3 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0165 article-title: Flood susceptibility modelling using advanced ensemble machine learning models publication-title: Geoscience Frontiers doi: 10.1016/j.gsf.2020.09.006 – volume: 208 start-page: 199 year: 2019 ident: 10.1016/j.eswa.2024.124311_b0010 article-title: Predictive analytics for hospital admissions from the emergency department using triage information publication-title: International Journal of Production Economics doi: 10.1016/j.ijpe.2018.11.024 – volume: 159 start-page: 473 year: 2018 ident: 10.1016/j.eswa.2024.124311_b0130 article-title: Neural network and particle swarm optimization for predicting the unconfined compressive strength of cemented paste backfill publication-title: Construction and Building Materials doi: 10.1016/j.conbuildmat.2017.11.006 – volume: 8 start-page: 518 issue: 5 year: 2020 ident: 10.1016/j.eswa.2024.124311_b0150 article-title: Planning and provision of ECMO services for severe ARDS during the COVID-19 pandemic and other outbreaks of emerging infectious diseases publication-title: The Lancet Respiratory Medicine doi: 10.1016/S2213-2600(20)30121-1 – volume: 42 start-page: 319 issue: 3 year: 2022 ident: 10.1016/j.eswa.2024.124311_b0075 article-title: Design of a machine learning to classify health beverages preferences for elderly people: An empirical study during COVID-19 in Thailand publication-title: International Journal of Industrial and Systems Engineering doi: 10.1504/IJISE.2022.126984 – volume: 81 year: 2019 ident: 10.1016/j.eswa.2024.124311_b0060 article-title: Performance measurement of airports using data envelopment analysis: A review of methods and findings publication-title: Journal of Air Transport Management doi: 10.1016/j.jairtraman.2019.101707 – volume: 13 start-page: 11 issue: 1 year: 2023 ident: 10.1016/j.eswa.2024.124311_b0145 article-title: Disease X vaccine production and supply chains: Risk assessing healthcare systems operating with artificial intelligence and industry 4.0 publication-title: Health and Technology (Berl) doi: 10.1007/s12553-022-00722-2 – volume: 56 start-page: 95 year: 2018 ident: 10.1016/j.eswa.2024.124311_b0210 article-title: A safety vulnerability assessment for chemical enterprises: A hybrid of a data envelopment analysis and fuzzy decision-making publication-title: Journal of Loss Prevention in the Process Industries doi: 10.1016/j.jlp.2018.08.018 – volume: 90 year: 2020 ident: 10.1016/j.eswa.2024.124311_b0065 article-title: Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization publication-title: Engineering Applications of Artificial Intelligence doi: 10.1016/j.engappai.2020.103541 – volume: 134 start-page: 812 issue: 6 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0100 article-title: SARS-CoV-2 infection hospitalization rate and infection fatality rate among the non-congregate population in connecticut publication-title: The American Journal of Medicine doi: 10.1016/j.amjmed.2021.01.020 – volume: 245 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0030 article-title: Estimation of daily maize transpiration using support vector machines, extreme gradient boosting, artificial and deep neural networks models publication-title: Agricultural Water Management doi: 10.1016/j.agwat.2020.106547 – volume: 9 issue: 4 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0105 article-title: Multiclass confusion matrix reduction method and its application on net promoter score classification problem publication-title: Technologies doi: 10.3390/technologies9040081 – volume: 124 start-page: 31 year: 2022 ident: 10.1016/j.eswa.2024.124311_b0160 article-title: Generalized SIR (GSIR) epidemic model: An improved framework for the predictive monitoring of COVID-19 pandemic publication-title: ISA Transactions doi: 10.1016/j.isatra.2021.02.016 – volume: 35 start-page: 1625 issue: 4 year: 2018 ident: 10.1016/j.eswa.2024.124311_b0205 article-title: Prediction and optimization model of activated carbon double layer capacitors based on improved heuristic approach genetic algorithm neural network publication-title: Engineering Computations doi: 10.1108/EC-03-2017-0105 – volume: 5 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0050 article-title: Recognition of early blight and late blight diseases on potato leaves based on graph cut segmentation publication-title: Journal of Agriculture and Food Research doi: 10.1016/j.jafr.2021.100154 – volume: 133 start-page: 331 year: 2019 ident: 10.1016/j.eswa.2024.124311_b0040 article-title: Data envelopment analysis models with ratio data: A revisit publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2019.04.041 – volume: 9 start-page: 322 issue: 4 year: 2020 ident: 10.1016/j.eswa.2024.124311_b0135 article-title: Performance evaluation of transit signal priorities on bus transit corridor based on data envelopment analysis publication-title: International Journal of Transportation Science and Technology doi: 10.1016/j.ijtst.2020.03.004 – volume: 10 start-page: 2752 year: 2019 ident: 10.1016/j.eswa.2024.124311_b0035 article-title: Clinical features predicting mortality risk in patients with viral pneumonia: The MuLBSTA score publication-title: Frontiers in Microbiology doi: 10.3389/fmicb.2019.02752 – volume: 105 start-page: 682 issue: 4 year: 2020 ident: 10.1016/j.eswa.2024.124311_b0090 article-title: Inferring super-spreading from transmission clusters of COVID-19 in Hong Kong, Japan, and Singapore publication-title: The Journal of Hospital Infection doi: 10.1016/j.jhin.2020.05.027 – volume: 39 start-page: 40 year: 2019 ident: 10.1016/j.eswa.2024.124311_b0070 article-title: The development of cyber-physical framework for classifying health beverage flavor for the ageing society publication-title: Procedia Manufacturing doi: 10.1016/j.promfg.2020.01.226 – ident: 10.1016/j.eswa.2024.124311_b0185 – volume: 295 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0200 article-title: Predicting river dissolved oxygen time series based on stand-alone models and hybrid wavelet-based models publication-title: Journal of Environmental Management doi: 10.1016/j.jenvman.2021.113085 – volume: 2 start-page: 429 issue: 6 year: 1978 ident: 10.1016/j.eswa.2024.124311_b0015 article-title: Measuring the efficiency of decision making units publication-title: European Journal of Operational Research doi: 10.1016/0377-2217(78)90138-8 – volume: 182 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0020 article-title: Meteorological and human mobility data on predicting COVID-19 cases by a novel hybrid decomposition method with anomaly detection analysis: A case study in the capitals of Brazil publication-title: Expert Systems With Applications doi: 10.1016/j.eswa.2021.115190 – volume: 113 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0175 article-title: The transformation of a trade fair and exhibition centre into a field hospital for COVID-19 patients via multi-utility tunnels publication-title: Tunnelling and Underground Space Technology doi: 10.1016/j.tust.2021.103951 – volume: 33 start-page: 1655 issue: 5 year: 2020 ident: 10.1016/j.eswa.2024.124311_b0005 article-title: Design and implementation of an autonomous EGR cooling system using deep neural network prediction to reduce NOx emission and fuel consumption of diesel engine publication-title: Neural Computing and Applications doi: 10.1007/s00521-020-05104-1 – volume: 13 issue: 1 year: 2022 ident: 10.1016/j.eswa.2024.124311_b0095 article-title: Development of prediction model for phosphate in reservoir water system based machine learning algorithms publication-title: Ain Shams Engineering Journal doi: 10.1016/j.asej.2021.06.009 – volume: 33 start-page: 17621 issue: 24 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0110 article-title: Diagnosis of COVID-19 and non-COVID-19 patients by classifying only a single cough sound publication-title: Neural Computing and Applications doi: 10.1007/s00521-021-06346-3 – volume: 12 start-page: 923 issue: 5 year: 2022 ident: 10.1016/j.eswa.2024.124311_b0140 article-title: Advancing the cybersecurity of the healthcare system with self-optimising and self-adaptative artificial intelligence (part 2) publication-title: Health and Technology (Berl) doi: 10.1007/s12553-022-00691-6 – volume: 75 start-page: 55 year: 2014 ident: 10.1016/j.eswa.2024.124311_b0080 article-title: A decision support methodology with risk assessment on prediction of terrorism insurgency distribution range radius and elapsing time: An empirical case study in Thailand publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2014.06.003 – volume: 264 year: 2020 ident: 10.1016/j.eswa.2024.124311_b0180 article-title: A literature review of sustainable supplier evaluation with Data Envelopment Analysis publication-title: Journal of Cleaner Production doi: 10.1016/j.jclepro.2020.121672 – volume: 32 start-page: 828 year: 2018 ident: 10.1016/j.eswa.2024.124311_b0155 article-title: Prediction and optimization of mechanical strength of diffusion bonds using integrated ANN-GA approach with process variables and metallographic characteristics publication-title: Journal of Manufacturing Processes doi: 10.1016/j.jmapro.2018.04.015 – volume: 54 start-page: 1020 issue: 4 year: 2015 ident: 10.1016/j.eswa.2024.124311_b0085 article-title: The development of a decision support framework for a quantitative risk assessment in multimodal green logistics: An empirical study publication-title: International Journal of Production Research doi: 10.1080/00207543.2015.1041570 – volume: 131 issue: 3 year: 2020 ident: 10.1016/j.eswa.2024.124311_b0170 article-title: COVID-19: Epidemiological factors during aerosol-generating medical procedures publication-title: Anesthesia & Analgesia doi: 10.1213/ANE.0000000000005063 – volume: 232 year: 2021 ident: 10.1016/j.eswa.2024.124311_b0055 article-title: OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications publication-title: International Journal of Production Economics doi: 10.1016/j.ijpe.2020.107921 – volume: 31 start-page: 1825 issue: 8 year: 2020 ident: 10.1016/j.eswa.2024.124311_b0120 article-title: Activation functions selection for BP neural network model of ground surface roughness publication-title: Journal of Intelligent Manufacturing doi: 10.1007/s10845-020-01538-5 |
| SSID | ssj0017007 |
| Score | 2.4750779 |
| Snippet | The WHO has declared that the COVID-19 pandemic is a severe health crisis. Currently, variants of concern are delta and omicron, including sub-lineages of the... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 124311 |
| SubjectTerms | Data envelopment analysis Deep neural network Prediction of COVID-19 pandemic Risk assessment Tunicate swarm algorithm |
| Title | An intelligent risk assessment on prediction of COVID-19 pandemic using DNN and TSA: An empirical case study in Thailand |
| URI | https://dx.doi.org/10.1016/j.eswa.2024.124311 |
| Volume | 253 |
| WOSCitedRecordID | wos001247382700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1873-6793 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017007 issn: 0957-4174 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3Nb9MwFLfQxoEL34gxQD5wm1IlcRzb3KJtiCFUkFam3qLEdrauI43abPTP5zm2k_ChCZC4RJVVx5Xfr8_P7-P3EHqjq1RxqtKAUBBDIgkNCsXioKSCGwtByo6n4Owjm075fC4-u3DBpmsnwOqab7ei-a-ihjEQtimd_Qtx9y-FAfgMQocniB2efyT4rO44ICzPZmtzx4uef9MEB5q1ic54U_Hw09nJURCJg8b4k02q_HXnPziaTrvIwuw0c95D_bVZOEYROPssM63xl8wuioXrBDJ4-Q2FcuuIon0J3ShYPlL0543t8pW1F8VytR7SAq7AuD5fuOqRYrmEa3099lLEiSvX611nvnxmyFWyPkgWJJFt0zPRVgNzRoKU2baJXkXHllD4F3VvPQ-XE735Zjik4mQC5gpx2vtHGu1Ts5hZC0wYE6iGG_NuzKgATbibnRzPP_SxJxbaInv_41yplc0K_Hml35szIxNl9hDdd3cLnFlMPEJ3dP0YPfB9O7BT40_QNqvxCCLYQAQPEMGrGg8QwasKe4hgDxHcQQQDRDCMYIDIWwwv7QGCDUBwBxBYCXuAPEVf3h3PDt8HrgNHIEkYtkHElAm0ayqF5GXFJKVwHDKpIrBpyiKMVSELUXHNE1rCsVmmJU_hygB2ESGlIuQZ2qlXtX6OsFCEhyqmkoVFoqko4Z4Rp0KUTFcVWKV7KPIbmUtHT2-6pFzlPg_xMjebn5vNz-3m76GDfk5jyVlu_Tb18smdeWnNxhzgdMu8F_84bx_dG_4JL9FOu77Wr9BdedMuNuvXDnXfAUMnnsA |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=An+intelligent+risk+assessment+on+prediction+of+COVID-19+pandemic+using+DNN+and+TSA%3A+An+empirical+case+study+in+Thailand&rft.jtitle=Expert+systems+with+applications&rft.au=Kengpol%2C+Athakorn&rft.au=Klunngien%2C+Jakkarin&rft.date=2024-11-01&rft.pub=Elsevier+Ltd&rft.issn=0957-4174&rft.eissn=1873-6793&rft.volume=253&rft_id=info:doi/10.1016%2Fj.eswa.2024.124311&rft.externalDocID=S0957417424011771 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0957-4174&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0957-4174&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0957-4174&client=summon |