IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i21p4480-d1270054.html
   My bibliography  Save this article

Morlet Wavelet Neural Network Investigations to Present the Numerical Investigations of the Prediction Differential Model

Author

Listed:
  • Zulqurnain Sabir

    (Department of Computer Science and Mathematics, Lebanese American University, Beirut 1401, Lebanon)

  • Adnène Arbi

    (Laboratory of Engineering Mathematics (LR01ES13), Tunisia Polytechnic School, University of Carthage, Tunis 2078, Tunisia
    Department of Advanced Sciences and Technologies at National School of Advanced Sciences and Technologies of Borj Cedria, University of Carthage, Hammam-Chott 1164, Tunisia)

  • Atef F. Hashem

    (Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia
    Department of Mathematics and Information Science, Faculty of Science, Beni-Suef University, Beni-Suef 62514, Egypt)

  • Mohamed A Abdelkawy

    (Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia
    Department of Mathematics and Information Science, Faculty of Science, Beni-Suef University, Beni-Suef 62514, Egypt)

Abstract

In this study, a design of Morlet wavelet neural networks (MWNNs) is presented to solve the prediction differential model (PDM) by applying the global approximation capability of a genetic algorithm (GA) and local quick interior-point algorithm scheme (IPAS), i.e., MWNN-GAIPAS. The famous and historical PDM is known as a variant of the functional differential system that works as theopposite of the delay differential models. A fitness function is constructed by using the mean square error and optimized through the GA-IPAS for solving the PDM. Three PDM examples have been presented numerically to check the authenticity of the MWNN-GAIPAS. For the perfection of the designed MWNN-GAIPAS, the comparability of the obtained outputs and exact results is performed. Moreover, the neuron analysis is performed by taking 3, 10, and 20 neurons. The statistical observations have been performed to authenticate the reliability of the MWNN-GAIPAS for solving the PDM.

Suggested Citation

  • Zulqurnain Sabir & Adnène Arbi & Atef F. Hashem & Mohamed A Abdelkawy, 2023. "Morlet Wavelet Neural Network Investigations to Present the Numerical Investigations of the Prediction Differential Model," Mathematics, MDPI, vol. 11(21), pages 1-20, October.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:21:p:4480-:d:1270054
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/21/4480/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/21/4480/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tian, Maoxi & El Khoury, Rim & Alshater, Muneer M., 2023. "The nonlinear and negative tail dependence and risk spillovers between foreign exchange and stock markets in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    2. Zou, Dexuan & Li, Steven & Kong, Xiangyong & Ouyang, Haibin & Li, Zongyan, 2019. "Solving the combined heat and power economic dispatch problems by an improved genetic algorithm and a new constraint handling strategy," Applied Energy, Elsevier, vol. 237(C), pages 646-670.
    3. Mayer, Martin János & Szilágyi, Artúr & Gróf, Gyula, 2020. "Environmental and economic multi-objective optimization of a household level hybrid renewable energy system by genetic algorithm," Applied Energy, Elsevier, vol. 269(C).
    4. Zulqurnain Sabir & Juan L. G. Guirao & Tareq Saeed & Fevzi Erdoğan, 2020. "Design of a Novel Second-Order Prediction Differential Model Solved by Using Adams and Explicit Runge–Kutta Numerical Methods," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-7, July.
    5. Sabir, Zulqurnain & Wahab, Hafiz Abdul & Umar, Muhammad & Erdoğan, Fevzi, 2019. "Stochastic numerical approach for solving second order nonlinear singular functional differential equation," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Benedek Kiss & Jose Dinis Silvestre & Rita Andrade Santos & Zsuzsa Szalay, 2021. "Environmental and Economic Optimisation of Buildings in Portugal and Hungary," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
    2. Sadeghian, Omid & Mohammadpour Shotorbani, Amin & Mohammadi-Ivatloo, Behnam & Sadiq, Rehan & Hewage, Kasun, 2021. "Risk-averse maintenance scheduling of generation units in combined heat and power systems with demand response," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    3. Rizk-Allah, Rizk M. & Hassanien, Aboul Ella & Snášel, Václav, 2022. "A hybrid chameleon swarm algorithm with superiority of feasible solutions for optimal combined heat and power economic dispatch problem," Energy, Elsevier, vol. 254(PC).
    4. Chen, Bin-xia & Sun, Yan-lin, 2024. "Risk characteristics and connectedness in cryptocurrency markets: New evidence from a non-linear framework," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    5. Bouri, Elie & Kamal, Elham & Kinateder, Harald, 2023. "FTX Collapse and systemic risk spillovers from FTX Token to major cryptocurrencies," Finance Research Letters, Elsevier, vol. 56(C).
    6. Xie, Xin & Mirza, Nawazish & Umar, Muhammad & Ji, Xiaoman, 2024. "Covid-19 and market discipline: Evidence from the banking sector in emerging markets," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 612-621.
    7. Chen, Bin-xia & Sun, Yan-lin, 2024. "Financial market connectedness between the U.S. and China: A new perspective based on non-linear causality networks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    8. Donghui Wang & Chunming Liu, 2019. "Combination Optimization Configuration Method of Capacitance and Resistance Devices for Suppressing DC Bias in Transformers," Energies, MDPI, vol. 12(9), pages 1-13, May.
    9. Zou, Dexuan & Gong, Dunwei & Ouyang, Haibin, 2023. "The dynamic economic emission dispatch of the combined heat and power system integrated with a wind farm and a photovoltaic plant," Applied Energy, Elsevier, vol. 351(C).
    10. Singh, Pushpendra & Meena, Nand K. & Yang, Jin & Vega-Fuentes, Eduardo & Bishnoi, Shree Krishna, 2020. "Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks," Applied Energy, Elsevier, vol. 278(C).
    11. Shaobin Zhang & Baofeng Shi, 2024. "The Asymmetric Tail Risk Spillover from the International Soybean Market to China’s Soybean Industry Chain," Agriculture, MDPI, vol. 14(7), pages 1-16, July.
    12. Jiang, Jianhua & Zhou, Renjie & Xu, Hao & Wang, Hao & Wu, Ping & Wang, Zhuo & Li, Jian, 2022. "Optimal sizing, operation strategy and case study of a grid-connected solid oxide fuel cell microgrid," Applied Energy, Elsevier, vol. 307(C).
    13. Morteza Nazari-Heris & Atefeh Tamaskani Esfehankalateh & Pouya Ifaei, 2023. "Hybrid Energy Systems for Buildings: A Techno-Economic-Enviro Systematic Review," Energies, MDPI, vol. 16(12), pages 1-15, June.
    14. Chen, Ning & Li, Shaofang & Lu, Shuai, 2023. "The extreme risk connectedness of the global financial system: G7 and BRICS evidence," Journal of Multinational Financial Management, Elsevier, vol. 69(C).
    15. José Luis Torres-Madroñero & Joham Alvarez-Montoya & Daniel Restrepo-Montoya & Jorge Mario Tamayo-Avendaño & César Nieto-Londoño & Julián Sierra-Pérez, 2020. "Technological and Operational Aspects That Limit Small Wind Turbines Performance," Energies, MDPI, vol. 13(22), pages 1-39, November.
    16. Kim, Taewan & Song, Jeonghwan & You, Donghyun, 2024. "Optimization of a wind farm layout to mitigate the wind power intermittency," Applied Energy, Elsevier, vol. 367(C).
    17. Chen, Bin-xia & Sun, Yan-lin, 2023. "Extreme risk contagion between international crude oil and China's energy-intensive sectors: New evidence from quantile Granger causality and spillover methods," Energy, Elsevier, vol. 285(C).
    18. Myada Shadoul & Rashid Al Abri & Hassan Yousef & Abdullah Al Shereiqi, 2024. "Designing a Dispatch Engine for Hybrid Renewable Power Stations Using a Mixed-Integer Linear Programming Technique," Energies, MDPI, vol. 17(13), pages 1-27, July.
    19. Wang, Chen & Guo, Su & Pei, Huanjin & He, Yi & Liu, Deyou & Li, Mengying, 2023. "Rolling optimization based on holism for the operation strategy of solar tower power plant," Applied Energy, Elsevier, vol. 331(C).
    20. Sabir, Zulqurnain & Saoud, Sahar & Raja, Muhammad Asif Zahoor & Wahab, Hafiz Abdul & Arbi, Adnène, 2020. "Heuristic computing technique for numerical solutions of nonlinear fourth order Emden–Fowler equation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 178(C), pages 534-548.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:21:p:4480-:d:1270054. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.