Numerical solutions of the Wolbachia invasive model using Levenberg-Marquardt backpropagation neural network technique
The current study presents the numerical solutions of the Wolbachia invasive model (WIM) using the neural network Levenberg-Marquardt (NN-LM) backpropagation technique. The dynamics of the Wolbachia model is categorized into four classes, namely Wolbachia-uninfected aquatic mosquitoes (An∗), Wolbach...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-07-01
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| Series: | Results in Physics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211379723003959 |
| _version_ | 1797802244353032192 |
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| author | Zeshan Faiz Shumaila Javeed Iftikhar Ahmed Dumitru Baleanu Muhammad Bilal Riaz Zulqurnain Sabir |
| author_facet | Zeshan Faiz Shumaila Javeed Iftikhar Ahmed Dumitru Baleanu Muhammad Bilal Riaz Zulqurnain Sabir |
| author_sort | Zeshan Faiz |
| collection | DOAJ |
| description | The current study presents the numerical solutions of the Wolbachia invasive model (WIM) using the neural network Levenberg-Marquardt (NN-LM) backpropagation technique. The dynamics of the Wolbachia model is categorized into four classes, namely Wolbachia-uninfected aquatic mosquitoes (An∗), Wolbachia-uninfected adult female mosquitoes (Fn∗), Wolbachia-infected aquatic mosquitoes (Aw∗), and Wolbachia-infected adult female mosquitoes (Fw∗). A reference dataset for the proposed NN-LM technique is created by solving the Wolbachia model using the Runge-Kutta (RK) numerical method. The reference dataset is used for validation, training, and testing of the proposed NN-LM technique for three different cases. The obtained numerical results from the proposed neural network technique are compared with the results obtained from the RK method for accuracy, correctness, and efficiency of the designed methodology. The validation of the proposed solution methodology is checked through the mean square error (MSE), error histograms, error plots, regression plots, and fitness plots. |
| first_indexed | 2024-03-13T05:03:02Z |
| format | Article |
| id | doaj.art-791482e8b4fc4310a7dd8b2a44a63db5 |
| institution | Directory Open Access Journal |
| issn | 2211-3797 |
| language | English |
| last_indexed | 2024-03-13T05:03:02Z |
| publishDate | 2023-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Physics |
| spelling | doaj.art-791482e8b4fc4310a7dd8b2a44a63db52023-06-17T05:18:17ZengElsevierResults in Physics2211-37972023-07-0150106602Numerical solutions of the Wolbachia invasive model using Levenberg-Marquardt backpropagation neural network techniqueZeshan Faiz0Shumaila Javeed1Iftikhar Ahmed2Dumitru Baleanu3Muhammad Bilal Riaz4Zulqurnain Sabir5Department of Mathematics, COMSATS University Islamabad, 45550 Islamabad Campus, Park Road, Chak Shahzad, Islamabad, PakistanDepartment of Mathematics, COMSATS University Islamabad, 45550 Islamabad Campus, Park Road, Chak Shahzad, Islamabad, Pakistan; Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon; Near East University, Mathematics Research Center, Department of Mathematics, Near East Boulevard, PC: 99138, Nicosia /Mersin 10, TurkeyNear East University, Mathematics Research Center, Department of Mathematics, Near East Boulevard, PC: 99138, Nicosia /Mersin 10, TurkeyDepartment of Mathematics, Cankaya University, Ankara Turkey; Institute of Space Sciences, Magurele-Bucharest, Romania; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 40402, Taiwan, Republic of ChinaFaculty of Applied Physics and Mathematics, Gdansk University of Technology, Poland; Department of Computer Science and Mathematics, Lebanese American University, Byblos, Lebanon; Corresponding author at: Faculty of Applied Physics and Mathematics, Gdansk University of Technology, Poland.Department of Mathematical Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab EmiratesThe current study presents the numerical solutions of the Wolbachia invasive model (WIM) using the neural network Levenberg-Marquardt (NN-LM) backpropagation technique. The dynamics of the Wolbachia model is categorized into four classes, namely Wolbachia-uninfected aquatic mosquitoes (An∗), Wolbachia-uninfected adult female mosquitoes (Fn∗), Wolbachia-infected aquatic mosquitoes (Aw∗), and Wolbachia-infected adult female mosquitoes (Fw∗). A reference dataset for the proposed NN-LM technique is created by solving the Wolbachia model using the Runge-Kutta (RK) numerical method. The reference dataset is used for validation, training, and testing of the proposed NN-LM technique for three different cases. The obtained numerical results from the proposed neural network technique are compared with the results obtained from the RK method for accuracy, correctness, and efficiency of the designed methodology. The validation of the proposed solution methodology is checked through the mean square error (MSE), error histograms, error plots, regression plots, and fitness plots.http://www.sciencedirect.com/science/article/pii/S2211379723003959WolbachiaNeural networkLevenberg-MarquardtMathematical modelMean square errorReference solutions |
| spellingShingle | Zeshan Faiz Shumaila Javeed Iftikhar Ahmed Dumitru Baleanu Muhammad Bilal Riaz Zulqurnain Sabir Numerical solutions of the Wolbachia invasive model using Levenberg-Marquardt backpropagation neural network technique Results in Physics Wolbachia Neural network Levenberg-Marquardt Mathematical model Mean square error Reference solutions |
| title | Numerical solutions of the Wolbachia invasive model using Levenberg-Marquardt backpropagation neural network technique |
| title_full | Numerical solutions of the Wolbachia invasive model using Levenberg-Marquardt backpropagation neural network technique |
| title_fullStr | Numerical solutions of the Wolbachia invasive model using Levenberg-Marquardt backpropagation neural network technique |
| title_full_unstemmed | Numerical solutions of the Wolbachia invasive model using Levenberg-Marquardt backpropagation neural network technique |
| title_short | Numerical solutions of the Wolbachia invasive model using Levenberg-Marquardt backpropagation neural network technique |
| title_sort | numerical solutions of the wolbachia invasive model using levenberg marquardt backpropagation neural network technique |
| topic | Wolbachia Neural network Levenberg-Marquardt Mathematical model Mean square error Reference solutions |
| url | http://www.sciencedirect.com/science/article/pii/S2211379723003959 |
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