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. 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.
    4. 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).
    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. He, Zhaoyu & Guo, Weimin & Zhang, Peng, 2022. "Performance prediction, optimal design and operational control of thermal energy storage using artificial intelligence methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    4. Fonseca, Juan D. & Commenge, Jean-Marc & Camargo, Mauricio & Falk, Laurent & Gil, Iván D., 2021. "Sustainability analysis for the design of distributed energy systems: A multi-objective optimization approach," Applied Energy, Elsevier, vol. 290(C).
    5. 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).
    6. 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).
    7. 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).
    8. 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.
    9. Ahmed Ginidi & Abdallah Elsayed & Abdullah Shaheen & Ehab Elattar & Ragab El-Sehiemy, 2021. "An Innovative Hybrid Heap-Based and Jellyfish Search Algorithm for Combined Heat and Power Economic Dispatch in Electrical Grids," Mathematics, MDPI, vol. 9(17), pages 1-25, August.
    10. Fatemeh Marzbani & Akmal Abdelfatah, 2024. "Economic Dispatch Optimization Strategies and Problem Formulation: A Comprehensive Review," Energies, MDPI, vol. 17(3), pages 1-31, January.
    11. Loau Al-Bahrani & Mehdi Seyedmahmoudian & Ben Horan & Alex Stojcevski, 2021. "Solving the Real Power Limitations in the Dynamic Economic Dispatch of Large-Scale Thermal Power Units under the Effects of Valve-Point Loading and Ramp-Rate Limitations," Sustainability, MDPI, vol. 13(3), pages 1-26, January.
    12. 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).
    13. Piotr Kułyk & Łukasz Augustowski, 2021. "Economic Profitability of a Hybrid Approach to Powering Residual Households from Natural Sources in Two Wind Zones of the Lubuskie Voivodeship in Poland," Energies, MDPI, vol. 14(21), pages 1-15, October.
    14. 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.
    15. 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).
    16. 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).
    17. Jadoon, Ihtesham & Raja, Muhammad Asif Zahoor & Junaid, Muhammad & Ahmed, Ashfaq & Rehman, Ata ur & Shoaib, Muhammad, 2021. "Design of evolutionary optimized finite difference based numerical computing for dust density model of nonlinear Van-der Pol Mathieu’s oscillatory systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 181(C), pages 444-470.
    18. Esmeralda López-Garza & René Fernando Domínguez-Cruz & Fernando Martell-Chávez & Iván Salgado-Tránsito, 2022. "Fuzzy Logic and Linear Programming-Based Power Grid-Enhanced Economical Dispatch for Sustainable and Stable Grid Operation in Eastern Mexico," Energies, MDPI, vol. 15(11), pages 1-18, June.
    19. Paramjeet Kaur & Krishna Teerth Chaturvedi & Mohan Lal Kolhe, 2023. "Combined Heat and Power Economic Dispatching within Energy Network using Hybrid Metaheuristic Technique," Energies, MDPI, vol. 16(3), pages 1-17, January.
    20. 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.

    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.