توظيف الشبكات العصبية المتكررة للتنبؤ بسعر صرف الدولار بالسوق العراقي الموازي
الشريط الجانبي للمقالة
THIS IS AN OPEN ACCESS ARTICLE UNDER THE CC BY LICENSE
محتوى المقالة الرئيسي
الملخص
في هذه الدراسة، تم استخدام الشبكات العصبية المتكررة للتنبؤ بسعر الدولار بالدينار العراقي، حيث يتضح أن جهود الحكومة للسيطرة على الأسعار في الأسواق الموازية، شهدت الأسواق التجارية تراجعا في سعر الصرف، لكنها ارتفع مرة أخرى، مما يشير إلى مشكلة اقتصادية لا تزال موجودة في البلاد. رغم تعديل سعر صرف الدينار، فإن أزمة الدولار في العراق لم تنته بعد. هنا نريد خلال الثلاثين يومًا القادمة أن ترتفع القيم المتوقعة للسعر اليومي للدولار مقابل الدينار العراقي أم لا، أفضل بنية لنموذج RNN كانت [1،10،1،1] باستخدام وظيفة التفعيل السوفت بلس، والتي تعطي أداء 85٪ لمجموعة بيانات التدريب و (92٪ و90٪) لمجموعات بيانات الاختبار والتحقق على التوالي، مع (Mse 0.018)، 0.000417)، و0.000477) للتدريب والاختبار والتحقق على التوالي في الحقبة الرابعة. نتائج القيم المتوقعة والتي تبدأ من 15 مايو 2023 حتى 13 يونيو 2023 سيكون سعر الدولار بين 1390 و1435.
التنزيلات
تفاصيل المقالة
المراجع
Ahmed, B. K., Rahim, S. A., Maaroof, B. B., & Taher, H. A. (2020). Comparison Between ARIMA And Fourier ARIMA Model to Forecast the Demand of Electricity in Sulaimani Governorate. Qalaai Zanist Journal, 5(3), 908-940.
Ahmed, Nawzad, M, (2007), “Forecasting water Inflow and Electric Power Generation in Darbandi-khan Station by Using FFNN, and Adaptive Method in Time series”, Doctorate Thesis, Statistics Dept., Administration and economics college, Sulaimani, Iraq.
Ahmed, Farhad, A, (2014), “Using FFNN and NARX models to Forecast daily temperature in Sulaimani”, MSc Thesis, Statistics Dept., Administration and economics college, Sulaimani, Iraq.
Alex Graves, (2008), “Supervised Sequence Labelling with Recurrent Neural Networks”, Technische Universita ̈t Mu ̈nchen Fakulta ̈t fu ̈r Informatik, PhD. Thesis.
Asraa, A., Rodeen, W., & Tahir, H., (2018). Forecasting the Impact of Waste on Environmental Pollution. International Journal of Sustainable Development and Science, 1(1), 1-12.
D. Zhang, Q. Jiang and X. Li, "Application of Neural Networks inFinancial Data Mining," International Journal of Information and Mathematical Sciences, vol. 1, pp. 106–109, Spring 2005.
M. Adya and F. Collopy, "How Effective are Neural Networks at Forecasting and Prediction? A Review and Evaluation," Journal of Forecasting, vol. 17, pp. 481–495, September – November 1998.
M. P. Wallace, "Neural Networks and Their Application to Finance," Business Intelligence Journal, vol. 1, pp. 67–77, July 2008.
M. Thenmozhi, "Forecasting Stock Index Returns Using Neural Networks," Delhi Business Review, vol. 7, pp. 59–69, July December 2006.
R. Lawrence, "Using Neural Networks to Forecast Stock Market Prices," Department of Computer Science, University of Manitoba, Winnipeg, Canada, Tech. Rep., Dec. 1997, Available: https: //people.ok.ubc.ca/rlawrenc/research/Papers/nn.pdf.
Sutskever, Ilya, (2013), “Training Recurrent Neural Networks”, a thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Computer Science University of Toronto.
Taher, H. A., & Ahmed, N. M., (2023). Using Bayesian Regression Neural Networks Model to Predict Thrombosis for Covid-19 Patients. resmilitaris, 13(1), 2077-2087.
Yu. Hao, (2010), “Levenberg–Marquardt Training”, Bogdan M. Wilamowski, Auburn University.
Kh, A. M., & Kh, A. A., (2022). application Deep learning to Predict crypto currency Prices and their relationship to Market adequacy (applied research bitcoin as an example). Финансы: теория и практика, 26(4), 95-108.
Abdalhammed M.K., Ghazal A.M., Ibrahim H.M., Ahmed A.K. Application Deep Learning to Predict Crypto Currency Prices and their Relationship to Market Adequacy (Applied Research Bitcoin as an Example). Finance: Theory and Practice. 2022;26(4):95-108. https://doi.org/10.26794/2587-5671-2022-26-4-95-108
Askar, A. J., Battal, A. H., & Hamad, A. A., (2023). Forecasting foreign reserves in the Central Bank of Iraq until 2025. Tikrit Journal of Administration and Economics Sciences, 19(61 part 1).
Al-Mashhadani, B. N., (2022). The Role of the Internal Auditor in Predicting Expected Credit Losses Suggested Procedures for Implementation in Banks Listed in the Iraq Stock Exchange. Tikrit Journal of Administration and Economics Sciences, 18(57 part 1).
Abd-AlHassin, S. K., & Abd-Alreda, N. Y., (2023). Comparison between prediction of demand for electric power using artificial intelligence techniques and traditional methods (ARIMA) A case study in the diesel station north of Al-Amarah to generate electric power. Tikrit Journal of Administration and Economics Sciences, 19(61 part 2).