Integrated Neuro-Evolution-Based Computing Paradigm to Study the COVID-19 Transposition and Severity in Romania and Pakistan
Abstract Numerical treatment of the COVID-19 transposition and severity in Romania and Pakistan has been presented in this study, i.e., ANN-GA-SQP through artificial neural network genetic algorithms (ANN-GA) and sequential quadratic programming (SQP), a design of an integrated computational intelli...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2022-09-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-022-00133-1 |
| _version_ | 1818022371010805760 |
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| author | Muhammad Shoaib Marwan Abukhaled Saba Kainat Kottakkaran Sooppy Nisar Muhammad Asif Zahoor Raja Ghania Zubair |
| author_facet | Muhammad Shoaib Marwan Abukhaled Saba Kainat Kottakkaran Sooppy Nisar Muhammad Asif Zahoor Raja Ghania Zubair |
| author_sort | Muhammad Shoaib |
| collection | DOAJ |
| description | Abstract Numerical treatment of the COVID-19 transposition and severity in Romania and Pakistan has been presented in this study, i.e., ANN-GA-SQP through artificial neural network genetic algorithms (ANN-GA) and sequential quadratic programming (SQP), a design of an integrated computational intelligent paradigm, COVID-19 is widely considered to be the greatest health threat humanity has ever faced. In terms of both health and economics, COVID-19 is a huge disaster. Many academics have looked at the COVID-19 model in their research papers, although they use different traditional techniques to represent it. The use of hybrid suggested solutions to solve this issue in the present article is significant, demonstrating the study's novelty. The SIR model of COVID-19 consists of a susceptible, infectious, and recovered class of population. The activation function for the construction of functions based on fitness in mean squared error sense is developed using nonlinear equations of the COVID-19 SIR model for the best performance of ANN-GA-SQP with the combined potential of GA and SQP of a network. While detailed refining is done with efficient local search with SQP, GAs operates as a global search. In addition, a neuron analysis will be presented to verify the effectiveness and complexity of the proposed method. Adam’s numerical methodology is applied to compare the sustainability and efficacy of the presented paradigm. Analytical evaluations of mean, median, and semi-interquartile range values, as well as Theil’s inequality coefficients, root mean squared error, and mean of absolute deviation) values have been observed. The convergence and correctness of the ANN-GA-SQP approach are further validated by statistical analyses. |
| first_indexed | 2024-04-14T08:31:40Z |
| format | Article |
| id | doaj.art-ed399727c67a47358b8fc350f5070af0 |
| institution | Directory Open Access Journal |
| issn | 1875-6883 |
| language | English |
| last_indexed | 2024-04-14T08:31:40Z |
| publishDate | 2022-09-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj.art-ed399727c67a47358b8fc350f5070af02022-12-22T02:03:54ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832022-09-0115111710.1007/s44196-022-00133-1Integrated Neuro-Evolution-Based Computing Paradigm to Study the COVID-19 Transposition and Severity in Romania and PakistanMuhammad Shoaib0Marwan Abukhaled1Saba Kainat2Kottakkaran Sooppy Nisar3Muhammad Asif Zahoor Raja4Ghania Zubair5Department of Mathematics, COMSATS University IslamabadDepartment of Mathematics and Statistics, American University of SharjahDepartment of Mathematics, COMSATS University IslamabadDepartment of Mathematics, College of Arts and Sciences, Prince Sattam bin Abdulaziz UniversityFuture Technology Research Center, National Yunlin University of Science and TechnologyDepartment of Mathematics, COMSATS University IslamabadAbstract Numerical treatment of the COVID-19 transposition and severity in Romania and Pakistan has been presented in this study, i.e., ANN-GA-SQP through artificial neural network genetic algorithms (ANN-GA) and sequential quadratic programming (SQP), a design of an integrated computational intelligent paradigm, COVID-19 is widely considered to be the greatest health threat humanity has ever faced. In terms of both health and economics, COVID-19 is a huge disaster. Many academics have looked at the COVID-19 model in their research papers, although they use different traditional techniques to represent it. The use of hybrid suggested solutions to solve this issue in the present article is significant, demonstrating the study's novelty. The SIR model of COVID-19 consists of a susceptible, infectious, and recovered class of population. The activation function for the construction of functions based on fitness in mean squared error sense is developed using nonlinear equations of the COVID-19 SIR model for the best performance of ANN-GA-SQP with the combined potential of GA and SQP of a network. While detailed refining is done with efficient local search with SQP, GAs operates as a global search. In addition, a neuron analysis will be presented to verify the effectiveness and complexity of the proposed method. Adam’s numerical methodology is applied to compare the sustainability and efficacy of the presented paradigm. Analytical evaluations of mean, median, and semi-interquartile range values, as well as Theil’s inequality coefficients, root mean squared error, and mean of absolute deviation) values have been observed. The convergence and correctness of the ANN-GA-SQP approach are further validated by statistical analyses.https://doi.org/10.1007/s44196-022-00133-1Numerical treatmentCOVID-19 transmissionArtificial neural networksGenetic algorithmsSequential quadratic programming |
| spellingShingle | Muhammad Shoaib Marwan Abukhaled Saba Kainat Kottakkaran Sooppy Nisar Muhammad Asif Zahoor Raja Ghania Zubair Integrated Neuro-Evolution-Based Computing Paradigm to Study the COVID-19 Transposition and Severity in Romania and Pakistan International Journal of Computational Intelligence Systems Numerical treatment COVID-19 transmission Artificial neural networks Genetic algorithms Sequential quadratic programming |
| title | Integrated Neuro-Evolution-Based Computing Paradigm to Study the COVID-19 Transposition and Severity in Romania and Pakistan |
| title_full | Integrated Neuro-Evolution-Based Computing Paradigm to Study the COVID-19 Transposition and Severity in Romania and Pakistan |
| title_fullStr | Integrated Neuro-Evolution-Based Computing Paradigm to Study the COVID-19 Transposition and Severity in Romania and Pakistan |
| title_full_unstemmed | Integrated Neuro-Evolution-Based Computing Paradigm to Study the COVID-19 Transposition and Severity in Romania and Pakistan |
| title_short | Integrated Neuro-Evolution-Based Computing Paradigm to Study the COVID-19 Transposition and Severity in Romania and Pakistan |
| title_sort | integrated neuro evolution based computing paradigm to study the covid 19 transposition and severity in romania and pakistan |
| topic | Numerical treatment COVID-19 transmission Artificial neural networks Genetic algorithms Sequential quadratic programming |
| url | https://doi.org/10.1007/s44196-022-00133-1 |
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