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Design of Morlet wavelet neural network to solve the non-linear influenza disease system

Zulqurnain Sabir

Zulqurnain Sabir

Department of Mathematics and Statistics, Hazara UniversityMansehra, Pakistan
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Sabir, Zulqurnain
, 
Muhammad Umar

Muhammad Umar

Department of Mathematics and Statistics, Hazara UniversityMansehra, Pakistan
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Umar, Muhammad
, 
Muhammad Asif Zahoor Raja

Muhammad Asif Zahoor Raja

Future Technology Research Center, National Yunlin University of Science and TechnologyTaiwan
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Raja, Muhammad Asif Zahoor
, 
Irwan Fathurrochman

Irwan Fathurrochman

Department of Islamic Educational Management, Institute of Agama Islam Negeri CurupRejang Lebong, Indonesia
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Fathurrochman, Irwan
 und 
Samer M. Shorman

Samer M. Shorman

Department of Accounting and Finance, Faculty of Administrative Sciences, Applied Science UniversityBahrain
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Shorman, Samer M.
  
27. Dez. 2021
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Online veröffentlicht: 27. Dez. 2021
Seitenbereich: 2033 - 2048
Eingereicht: 17. Juni 2021
Akzeptiert: 24. Sept. 2021
DOI: https://doi.org/10.2478/amns.2021.2.00120
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© 2023 Zulqurnain Sabir et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Proposed framework of MWNNs using the GA-SQP to solve the biological-based NIDS. GA, genetic algorithm; MWNNs, Morlet wavelet neural networks; SQP, sequential quadratic programming.
Proposed framework of MWNNs using the GA-SQP to solve the biological-based NIDS. GA, genetic algorithm; MWNNs, Morlet wavelet neural networks; SQP, sequential quadratic programming.

Fig. 2

Best weight vectors set and best/mean results comparison with reference solutions to solve NIDS. NIDS, non-linear influenza disease system.
Best weight vectors set and best/mean results comparison with reference solutions to solve NIDS. NIDS, non-linear influenza disease system.

Fig. 3

Best and mean values of the AE for each group of NIDS. AE, absolute error; NIDS, non-linear influenza disease system.
Best and mean values of the AE for each group of NIDS. AE, absolute error; NIDS, non-linear influenza disease system.

Fig. 4

Statistical performances based on EVAF, MAD and TIC operators for solving NIDS. MAD, mean absolute deviation; NIDS, non-linear influenza disease system; TIC, Theil’s inequality coefficient.
Statistical performances based on EVAF, MAD and TIC operators for solving NIDS. MAD, mean absolute deviation; NIDS, non-linear influenza disease system; TIC, Theil’s inequality coefficient.

Fig. 5

Convergence performances based on TIC, EVAF and RMSE operators for solving NIDS. NIDS, non-linear influenza disease system.
Convergence performances based on TIC, EVAF and RMSE operators for solving NIDS. NIDS, non-linear influenza disease system.
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