IDEAS home Printed from https://ideas.repec.org/a/ibn/masjnl/v13y2022i2p157.html

Fuzzy Logic and Back-Propagation Neural Networks for Optimal Performance

Author

Listed:
  • Abbas Al-Refaie
  • Rami Fouad
  • Raed Athamneh

Abstract

Thus far, the Taguchi technique is found only efficient in obtaining the combination of optimal factor settings when a single product/process response is considered. In today’s dynamic environment, customers are interested in multiple quality responses. This research, therefore, utilizes fuzzy logic and backward-propagation neural networks (BPNNs) to optimize process performance for products of multiple quality responses. In this research, quality characteristics are transformed to signal to noise (S/N) ratios, which are then used as inputs to a fuzzy model to obtain a single common output measure (COM). Next, BPNNs are employed to obtain full-factorial experimental data. Finally, the combination of factor levels that maximizes the average COM value is chosen as the optimal combination. Three case studies are provided for illustration; in all of which the proposed approach provided the largest total anticipated improvement. This indicates that the proposed approach is more efficient than Taguchi-fuzzy, grey-Taguchi, and Taguchi-utility methods. In conclusion, the fuzzy-BPNN approach may greatly assist process/product engineers in optimizing performance with multiple responses in a wide range of business applications.

Suggested Citation

  • Abbas Al-Refaie & Rami Fouad & Raed Athamneh, 2019. "Fuzzy Logic and Back-Propagation Neural Networks for Optimal Performance," Modern Applied Science, Canadian Center of Science and Education, vol. 13(2), pages 157-157, February.
    • Handle: RePEc:ibn:masjnl:v:13:y:2022:i:2:p:157
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/mas/article/download/0/0/38181/38689
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/mas/article/view/0/38181
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Abbas Al-Refaie, 2012. "Optimizing performance with multiple responses using cross-evaluation and aggressive formulation in data envelopment analysis," IISE Transactions, Taylor & Francis Journals, vol. 44(4), pages 262-276.
    2. Sivasakthivel, T. & Murugesan, K. & Sahoo, P.K., 2014. "Optimization of ground heat exchanger parameters of ground source heat pump system for space heating applications," Energy, Elsevier, vol. 78(C), pages 573-586.
    3. Mandic, Ksenija & Delibasic, Boris & Knezevic, Snezana & Benkovic, Sladjana, 2014. "Analysis of the financial parameters of Serbian banks through the application of the fuzzy AHP and TOPSIS methods," Economic Modelling, Elsevier, vol. 43(C), pages 30-37.
    4. Chen, S.X. & Gooi, H.B. & Wang, M.Q., 2013. "Solar radiation forecast based on fuzzy logic and neural networks," Renewable Energy, Elsevier, vol. 60(C), pages 195-201.
    5. Abbas Al-Refaie & Ibrahim Rawabdeh & Reema Abu-alhaj & Issam S. Jalham, 2012. "A Fuzzy Multiple Regression Approach for Optimizing Multiple Responses in the Taguchi Method," International Journal of Fuzzy System Applications (IJFSA), IGI Global Scientific Publishing, vol. 2(3), pages 13-34, July.
    6. Bose, Probir Kumar & Deb, Madhujit & Banerjee, Rahul & Majumder, Arindam, 2013. "Multi objective optimization of performance parameters of a single cylinder diesel engine running with hydrogen using a Taguchi-fuzzy based approach," Energy, Elsevier, vol. 63(C), pages 375-386.
    7. Sivasakthivel, T. & Murugesan, K. & Thomas, H.R., 2014. "Optimization of operating parameters of ground source heat pump system for space heating and cooling by Taguchi method and utility concept," Applied Energy, Elsevier, vol. 116(C), pages 76-85.
    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. Noye, Sarah & Mulero Martinez, Rubén & Carnieletto, Laura & De Carli, Michele & Castelruiz Aguirre, Amaia, 2022. "A review of advanced ground source heat pump control: Artificial intelligence for autonomous and adaptive control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    2. Bin Yan & Qiuxuan Wu & Xiaoni Chi & Chenxi Wu & Ping Luo & Yanbin Luo & Pingliang Zeng, 2022. "Numerical and Experimental Investigation of Photovoltaic/Thermal Systems: Parameter Analysis and Determination of Optimum Flow," Sustainability, MDPI, vol. 14(16), pages 1-17, August.
    3. Somogyi, Viola & Sebestyén, Viktor & Nagy, Georgina, 2017. "Scientific achievements and regulation of shallow geothermal systems in six European countries – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 934-952.
    4. Sakr, Mohamed & Liu, Shuli, 2014. "A comprehensive review on applications of ohmic heating (OH)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 262-269.
    5. Vivek Aggarwal & Chandan Swaroop Meena & Ashok Kumar & Tabish Alam & Anuj Kumar & Arijit Ghosh & Aritra Ghosh, 2020. "Potential and Future Prospects of Geothermal Energy in Space Conditioning of Buildings: India and Worldwide Review," Sustainability, MDPI, vol. 12(20), pages 1-19, October.
    6. Ma, Zhenjun & Xia, Lei & Gong, Xuemei & Kokogiannakis, Georgios & Wang, Shugang & Zhou, Xinlei, 2020. "Recent advances and development in optimal design and control of ground source heat pump systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    7. Pandey, Navdeep & Murugesan, K. & Thomas, H.R., 2017. "Optimization of ground heat exchangers for space heating and cooling applications using Taguchi method and utility concept," Applied Energy, Elsevier, vol. 190(C), pages 421-438.
    8. Abbas Al-Refaie & Wafa’a Al-Alaween & Ali Diabat & Ming-Hsien Li, 2017. "Solving dynamic systems with multi-responses by integrating desirability function and data envelopment analysis," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 387-403, February.
    9. Pavel Neuberger & Radomír Adamovský, 2019. "Analysis and Comparison of Some Low-Temperature Heat Sources for Heat Pumps," Energies, MDPI, vol. 12(10), pages 1-14, May.
    10. Lin, Jian & Zhong, Xiaoyi & Wang, Jing & Huang, Yuan & Bai, Xuetao & Wang, Xiaonan & Shah, Nilay & Xie, Shan & Zhao, Yingru, 2021. "Relative optimization potential: A novel perspective to address trade-off challenges in urban energy system planning," Applied Energy, Elsevier, vol. 304(C).
    11. Alshehri, Faisal & Beck, Stephen & Ingham, Derek & Ma, Lin & Pourkashanian, Mohammed, 2021. "Sensitivity analysis of a vertical geothermal heat pump system in a hot dry climate," Renewable Energy, Elsevier, vol. 178(C), pages 785-801.
    12. Li, Jinghua & Fang, Jiakun & Zeng, Qing & Chen, Zhe, 2016. "Optimal operation of the integrated electrical and heating systems to accommodate the intermittent renewable sources," Applied Energy, Elsevier, vol. 167(C), pages 244-254.
    13. Sivasakthivel, T. & Murugesan, K. & Sahoo, P.K., 2015. "Study of technical, economical and environmental viability of ground source heat pump system for Himalayan cities of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 452-462.
    14. Al-Ameen, Yasameen & Ianakiev, Anton & Evans, Robert, 2018. "Recycling construction and industrial landfill waste material for backfill in horizontal ground heat exchanger systems," Energy, Elsevier, vol. 151(C), pages 556-568.
    15. Lin, Wenye & Ma, Zhenjun, 2016. "Using Taguchi-Fibonacci search method to optimize phase change materials enhanced buildings with integrated solar photovoltaic thermal collectors," Energy, Elsevier, vol. 106(C), pages 23-37.
    16. Mollahosseini, Arash & Hosseini, Seyed Amid & Jabbari, Mostafa & Figoli, Alberto & Rahimpour, Ahmad, 2017. "Renewable energy management and market in Iran: A holistic review on current state and future demands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 774-788.
    17. Paul Christodoulides & Christakis Christou & Georgios A. Florides, 2024. "Ground Source Heat Pumps in Buildings Revisited and Prospects," Energies, MDPI, vol. 17(13), pages 1-36, July.
    18. Xie, Yiwei & Hu, Pingfang & Zhu, Na & Lei, Fei & Xing, Lu & Xu, Linghong, 2020. "Collaborative optimization of ground source heat pump-radiant ceiling air conditioning system based on response surface method and NSGA-II," Renewable Energy, Elsevier, vol. 147(P1), pages 249-264.
    19. Xia, Lei & Ma, Zhenjun & Kokogiannakis, Georgios & Wang, Shugang & Gong, Xuemei, 2018. "A model-based optimal control strategy for ground source heat pump systems with integrated solar photovoltaic thermal collectors," Applied Energy, Elsevier, vol. 228(C), pages 1399-1412.
    20. Nie, S. & Huang, Z.C. & Huang, G.H. & Yu, L. & Liu, J., 2018. "Optimization of electric power systems with cost minimization and environmental-impact mitigation under multiple uncertainties," Applied Energy, Elsevier, vol. 221(C), pages 249-267.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    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:ibn:masjnl:v:13:y:2022:i:2:p:157. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.