التنبؤ بالشبكة العصبية الاصطناعية المهجنة بالخوارزمية الجينية الفوضوية / النفط العراقي انموذجا
الشريط الجانبي للمقالة
محتوى المقالة الرئيسي
الملخص
يعد التنبؤ أحد الطرائق العلمية والحديثة المطورة المستخدمة في عمليات التخطيط واتخاذ القرار، حيث تم في هذه الدراسة استخدام أسلوب جديد غير تقليدي للتنبؤ بالنفط في العراق باستخدام اسلوب الشبكة العصبية الاصطناعية وتهجينه مع الخوارزمية الجينية الفوضوية للتنبؤ بإنتاج وأسعار النفط العراقي. إذ ان استخدام أكثر من طريقة في التنبؤ يؤدي إلى زيادة دقة التقديرات المستقبلية، حيث تم الجمع بين أنموذجين هما الشبكة العصبية الاصطناعية والخوارزمية الجينية الفوضوية (CGANN)، توصلت الدراسة إلى ان النموذج المهجن (CGANN) يؤدي إلى تحسين دقة النموذج بشكل كبير والتغلب على نقاط الضعف بين النموذجين وجمع نقاط القوة لكليهما وإعطاء التنبؤ بالنفط العراقي حتى عام 2035 بشكل ادق.
تفاصيل المقالة
هذا العمل مرخص بموجب Creative Commons Attribution-ShareAlike 4.0 International License.
المراجع
The artificial neural network was used with the chaotic genetic algorithm and the results were shown as follows:
Chaotic Genetic Algorithm (CGA) is an excellent tool and efficient method for solving nonlinear and complex optimization problems.
Hybridizing the artificial neural network (ANN) with the chaotic genetic algorithm (CGA) makes the hybrid CGANN model more accurate and more efficient for predicting Iraqi oil.
The hybrid model (CGANN) leads to a significant improvement in the accuracy of the model, overcoming the weaknesses between the two models, combining the strengths of both, and providing a more accurate forecast of Iraqi oil until 2035.
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