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Analysis and Applications of Artificial Intelligence in Digital Education Based on Complex Fuzzy Clustering Algorithms

Author

Listed:
  • Majed Albaity

    (Department of Mathematics, Faculty of Science, King Abdulaziz University, P.O. Box 80348, Jeddah 22254, Saudi Arabia)

  • Tahir Mahmood

    (Department of Mathematics and Statistics, International Islamic University, Islamabad 44000, Pakistan)

  • Zeeshan Ali

    (Department of Mathematics and Statistics, International Islamic University, Islamabad 44000, Pakistan)

Abstract

Digital education is very important and valuable because it is a subpart of artificial intelligence, which is used in many real-life problems. Digital education is the modern utilization of digital techniques and tools during online purchasing, teaching, research, and learning and is often referred to as technology-enhanced learning or e-learning programs. Further, similarity measures (SM) and complex fuzzy (CF) logic are two different ideas that play a very valuable and dominant role in the environment of fuzzy decision theory. In this manuscript, we concentrate on utilizing different types of dice SM (D-SM) and generalized dice SM (GD-SM) in the environment of a CF set (CFS), called CF dice SM (CFD-SM), CF weighted dice SM (CFWD-SM), CF generalized dice SM (CFGD-SM), and CF weighted generalized dice SM (CFWGD-SM), and also derived associated outcomes. Furthermore, to evaluate or state the supremacy and effectiveness of the derived measures, we aim to evaluate the application of artificial intelligence in digital education under the consideration of derived measures for CF information and try to verify them with the help of several examples. Finally, with the help of examples, we illustrate the comparison between the presented and existing measures to show the supremacy and feasibility of the derived measures.

Suggested Citation

  • Majed Albaity & Tahir Mahmood & Zeeshan Ali, 2023. "Analysis and Applications of Artificial Intelligence in Digital Education Based on Complex Fuzzy Clustering Algorithms," Mathematics, MDPI, vol. 11(14), pages 1-20, July.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:14:p:3184-:d:1198577
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    References listed on IDEAS

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    1. Wenping Guo & Lvqing Bi & Bo Hu & Songsong Dai, 2020. "Cosine Similarity Measure of Complex Fuzzy Sets and Robustness of Complex Fuzzy Connectives," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-9, July.
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