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Towards an Optimized Industrial Decision-Making Model Powered by Artificial Neural Networks

In: Information Systems and Technological Advances for Sustainable Development

Author

Listed:
  • Hala Mellouli

    (ENSAM, Hassan II University)

  • Anwar Meddaoui

    (ENSAM, Hassan II University)

  • Abdelhamid Zaki

    (ENSAM, Hassan II University)

Abstract

In today's digital age, many different variables can affect industrial decision-making, challenging companies’ ability to optimize performance and achieve success in a competitive market. To stay ahead of the game, companies must find ways to improve their decision-making processes. One solution is to use artificial intelligence (AI) to manage large amounts of data quickly and efficiently. By learning from previous experiences, AI can help ensure that decisions are accurate and reliable. In this paper, we introduce a hybrid decision-making model that combines artificial neural networks with the Analytic Hierarchy Process and the balanced scorecard. This approach is designed for complex industrial problems and provides real-time recommendations for the most accurate and effective decisions.

Suggested Citation

  • Hala Mellouli & Anwar Meddaoui & Abdelhamid Zaki, 2024. "Towards an Optimized Industrial Decision-Making Model Powered by Artificial Neural Networks," Lecture Notes in Information Systems and Organization, in: Mohamed Ben Ahmed & Anouar Abdelhakim Boudhir & Hany Farhat Abd Elhamid Attia & Adriana Eštoková & M (ed.), Information Systems and Technological Advances for Sustainable Development, pages 85-92, Springer.
    • Handle: RePEc:spr:lnichp:978-3-031-75329-9_10
    DOI: 10.1007/978-3-031-75329-9_10
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