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With the diversity of funding methods, the choice of the most appropriate of them is becoming more and more complex, particularly for industrial projects. This article uses deep learning to choose the best method of funding an industrial project in Morocco. The data covers 5198 industrial projects. The algorithms used are MLP and CNN. The results show that the CNN model performs better in terms of accuracy. The CNN model also demonstrates robust generalization. As for the MLP model, it shows an overall accuracy below 0.5, indicating the need for a larger amount of data.

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Predicting Funding Decisions for Industrial Projects Applying Deep Learning: Evidence from Morocco

  • 会议论文

  • 发表日期：

    2025年

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  • Soukaina Laaouina,
  • Mimoun Benali,
  • Abdelhamid El Bouhadi

摘要

With the diversity of funding methods, the choice of the most appropriate of them is becoming more and more complex, particularly for industrial projects. This article uses deep learning to choose the best method of funding an industrial project in Morocco. The data covers 5198 industrial projects. The algorithms used are MLP and CNN. The results show that the CNN model performs better in terms of accuracy. The CNN model also demonstrates robust generalization. As for the MLP model, it shows an overall accuracy below 0.5, indicating the need for a larger amount of data.