استخدام خوارزمية (ليفنبرغ ماركوارت) كدالة تنشيط للتنبؤ بمؤشر جودة المياه (WQI) في مدينة كاستامونو - تركيا

المؤلفون

  • إدريس بشير إمنيسي قسم تكنولوجيا المياه في المعهد العالي للتقنيات الزراعية، المرج، ليبيا.
  • ميراج أيدين جامعة قسطموني، كلية الدراسات العليا للعلوم الطبيعية والتطبيقية، قسم إدارة مستجمعات المياه، كلية الغابات، تركيا.

DOI:

https://doi.org/10.63359/8jfhe511

الكلمات المفتاحية:

الشبكات العصبية الاصطناعية، سد كاراجوماك، مؤشر جودة المياه

الملخص

استخدام الشبكة العصبية الاصطناعية (ANN) ( برنامج كمبيوتر) لاجراء تنبؤ (توقع) لمؤشر جودة المياه (WQI) في مدينة كاستامونا - تركيا. مؤشر جودة المياه يعطي وصف كامل لجودة المياه ضمن موقع محدد ووقت محدد اعتمادا علي بعض عوامل جودة المياه تمت خلال خمس سنوات (من يناير 2011 حتي ديسمبر 2015 ) طبقت شبكة التغذية المباشرة البسيطة باستخدام خوارزمية الانتشار الخلفي القياسية (Levenberg-Marquardt) (train-Lm) في النمؤذج. في هذه الدراسة ، تم استخدام طبقة مخفية واحدة للنمذجة مع عدد مختلف من الخلايا العصبية المخفية (n+ 1) و (2n+ 1) من عقد الإدخال. كشفت الدراسة التاثير المباشر لكمية الخلايا العصبية المخفية علي أداء النمؤذج ويمكننا أن نرى هذا النموذج لخوارزمية الانتشار الخلفي القياسية (Levenberg-Marquardt) كدالة تنشيط (train-Lm) هي الأمثل في الأداء للتنبؤ بمؤشر جودة المياه (WQI) مع خيارات فعالة للتنبؤ بجودة المياه السطحية وغيرها من المسطحات.

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التنزيلات

منشور

31.12.2019

كيفية الاقتباس

استخدام خوارزمية (ليفنبرغ ماركوارت) كدالة تنشيط للتنبؤ بمؤشر جودة المياه (WQI) في مدينة كاستامونو - تركيا. (2019). المجلة الليبية لعلوم وتكنولوجيا البيئة (م ل ع ت ب), 1(2), 2o - 29. https://doi.org/10.63359/8jfhe511

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