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IoT Technology Enabled Heuristic Model with Morlet wavelet neural network for numerical treatment of Heterogeneous Mosquito Release Ecosystem

The utmost advancements of artificial neural networks (ANNs), software-defined networks (SDNs) and internet of things (IoT) technologies find beneficial in different applications of the smart healthcare sector. Aiming at modern technology's use in the future development of healthcare, this pape...

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Main Authors: Zulqurnain Sabir, Kashif Nisar, Muhammad Asif Zahoor Raja, Muhammad Reazul Haque, Muhammad Umar, Ag. Asri Ag. Ibrahim, Le, Dac-Nhuong
Format: Article
Language:English
English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2021
Subjects:
QA71-90 Instruments and machines
Online Access:https://eprints.ums.edu.my/id/eprint/33083/3/IoT%20Technology%20Enabled%20Heuristic%20Model%20with%20Morlet%20wavelet%20neural%20network%20for%20numerical%20treatment%20of%20Heterogeneous%20Mosquito%20Release%20Ecosystem%20_ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/33083/5/IoT%20Technology%20Enabled%20Heuristic%20Model%20with%20Morlet%20wavelet%20neural%20network%20for%20numerical%20treatment%20of%20Heterogeneous%20Mosquito%20Release%20Ecosystem.pdf
https://eprints.ums.edu.my/id/eprint/33083/
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9541162
https://doi.org/10.1109/ACCESS.2021.3113986
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spelling my.ums.eprints.330832022-07-12T00:41:25Z https://eprints.ums.edu.my/id/eprint/33083/ IoT Technology Enabled Heuristic Model with Morlet wavelet neural network for numerical treatment of Heterogeneous Mosquito Release Ecosystem Zulqurnain Sabir Kashif Nisar Muhammad Asif Zahoor Raja Muhammad Reazul Haque Muhammad Umar Ag. Asri Ag. Ibrahim Le, Dac-Nhuong QA71-90 Instruments and machines The utmost advancements of artificial neural networks (ANNs), software-defined networks (SDNs) and internet of things (IoT) technologies find beneficial in different applications of the smart healthcare sector. Aiming at modern technology's use in the future development of healthcare, this paper presents an advanced heuristic based on Morlet wavelet neural network for solving the mosquito release ecosystem in a heterogeneous atmosphere. The mosquito release ecosystem is dependent of six classes, eggs density, larvae density, pupae density, mosquitoes searching for hosts density, resting mosquito’s density and mosquitoes searching for ovipositional site density. An artificial neural network with the layer structure of Morlet wavelet (MWNN) kernel is presented using the global and local search optimization schemes of genetic algorithm (GA) and active-set algorithm (ASA), i.e., MWNN-GA-ASA. The accurateness, reliability and constancy of the proposed MWNN-GA-ASA is established through comparative examinations with Adams method based numerical results to solve the proposed nonlinear system with matching of order 10-06 to 10-09. The accuracy and convergence of the proposed MWNN-GA-ASA is certified using the statistical operators based on root mean square error (RMSE), Theil's inequality coefficient (T.I.C) and mean absolute deviation (MAD) operators. Institute of Electrical and Electronics Engineers (IEEE) 2021 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/33083/3/IoT%20Technology%20Enabled%20Heuristic%20Model%20with%20Morlet%20wavelet%20neural%20network%20for%20numerical%20treatment%20of%20Heterogeneous%20Mosquito%20Release%20Ecosystem%20_ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/33083/5/IoT%20Technology%20Enabled%20Heuristic%20Model%20with%20Morlet%20wavelet%20neural%20network%20for%20numerical%20treatment%20of%20Heterogeneous%20Mosquito%20Release%20Ecosystem.pdf Zulqurnain Sabir and Kashif Nisar and Muhammad Asif Zahoor Raja and Muhammad Reazul Haque and Muhammad Umar and Ag. Asri Ag. Ibrahim and Le, Dac-Nhuong (2021) IoT Technology Enabled Heuristic Model with Morlet wavelet neural network for numerical treatment of Heterogeneous Mosquito Release Ecosystem. IEEE Access, 9. pp. 132897-132913. ISSN 2169-3536 https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9541162 https://doi.org/10.1109/ACCESS.2021.3113986
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic QA71-90 Instruments and machines
spellingShingle QA71-90 Instruments and machines
Zulqurnain Sabir
Kashif Nisar
Muhammad Asif Zahoor Raja
Muhammad Reazul Haque
Muhammad Umar
Ag. Asri Ag. Ibrahim
Le, Dac-Nhuong
IoT Technology Enabled Heuristic Model with Morlet wavelet neural network for numerical treatment of Heterogeneous Mosquito Release Ecosystem
description The utmost advancements of artificial neural networks (ANNs), software-defined networks (SDNs) and internet of things (IoT) technologies find beneficial in different applications of the smart healthcare sector. Aiming at modern technology's use in the future development of healthcare, this paper presents an advanced heuristic based on Morlet wavelet neural network for solving the mosquito release ecosystem in a heterogeneous atmosphere. The mosquito release ecosystem is dependent of six classes, eggs density, larvae density, pupae density, mosquitoes searching for hosts density, resting mosquito’s density and mosquitoes searching for ovipositional site density. An artificial neural network with the layer structure of Morlet wavelet (MWNN) kernel is presented using the global and local search optimization schemes of genetic algorithm (GA) and active-set algorithm (ASA), i.e., MWNN-GA-ASA. The accurateness, reliability and constancy of the proposed MWNN-GA-ASA is established through comparative examinations with Adams method based numerical results to solve the proposed nonlinear system with matching of order 10-06 to 10-09. The accuracy and convergence of the proposed MWNN-GA-ASA is certified using the statistical operators based on root mean square error (RMSE), Theil's inequality coefficient (T.I.C) and mean absolute deviation (MAD) operators.
format Article
author Zulqurnain Sabir
Kashif Nisar
Muhammad Asif Zahoor Raja
Muhammad Reazul Haque
Muhammad Umar
Ag. Asri Ag. Ibrahim
Le, Dac-Nhuong
author_facet Zulqurnain Sabir
Kashif Nisar
Muhammad Asif Zahoor Raja
Muhammad Reazul Haque
Muhammad Umar
Ag. Asri Ag. Ibrahim
Le, Dac-Nhuong
author_sort Zulqurnain Sabir
title IoT Technology Enabled Heuristic Model with Morlet wavelet neural network for numerical treatment of Heterogeneous Mosquito Release Ecosystem
title_short IoT Technology Enabled Heuristic Model with Morlet wavelet neural network for numerical treatment of Heterogeneous Mosquito Release Ecosystem
title_full IoT Technology Enabled Heuristic Model with Morlet wavelet neural network for numerical treatment of Heterogeneous Mosquito Release Ecosystem
title_fullStr IoT Technology Enabled Heuristic Model with Morlet wavelet neural network for numerical treatment of Heterogeneous Mosquito Release Ecosystem
title_full_unstemmed IoT Technology Enabled Heuristic Model with Morlet wavelet neural network for numerical treatment of Heterogeneous Mosquito Release Ecosystem
title_sort iot technology enabled heuristic model with morlet wavelet neural network for numerical treatment of heterogeneous mosquito release ecosystem
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2021
url https://eprints.ums.edu.my/id/eprint/33083/3/IoT%20Technology%20Enabled%20Heuristic%20Model%20with%20Morlet%20wavelet%20neural%20network%20for%20numerical%20treatment%20of%20Heterogeneous%20Mosquito%20Release%20Ecosystem%20_ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/33083/5/IoT%20Technology%20Enabled%20Heuristic%20Model%20with%20Morlet%20wavelet%20neural%20network%20for%20numerical%20treatment%20of%20Heterogeneous%20Mosquito%20Release%20Ecosystem.pdf
https://eprints.ums.edu.my/id/eprint/33083/
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9541162
https://doi.org/10.1109/ACCESS.2021.3113986
_version_ 1760231115345362944
score 13.222552

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