تستخدم الشبكة العصبية الصنعية طريقة تعلم استقرائي، و تتطلب بشكل عام أمثِلة
لبيانات التدريب، بينما تستخدم الخوارزمية الجينية تعلم اقتطاعي، و تتطلب تابع هدف. لقد تمّ
تنظيم التعاون بين هاتين التقانتين في دراستنا هذه بغرض تعزيز أداء كل تقانة من خلال بناء
نظام هجين منهما، عن طريق كتابة برمجيّة عامّة باستخدام برنامج MATLAB بغرض الاختيار الفعّال لمتحولات الدخل لعمليات التنبؤ، و أمثلة أوزان شبكة البيانات قيد الدراسة، و من ثمّ تطبيق هذه البرنامج على بيانات يوميّة، تمّ جمعها من حوض نهر الكبير الجنوبي هي (الهطول، التبخر، الحرارة، الرطوبة النسبية و الجريان النهري بتأخر زمني مقداره يوم واحد) بغرض التنبؤ بالجريان النهري.
This study has reached to that ANN (5-9-1) (five neurons in input
layer_nine neurons in hidden layer _ one neuron in output layer) is the
optimum artificial network that hybrid system has reached to it with
mean squared error equals (1*10^-4) (0.7 m3/sec), where this software
has summed up millions of experiments in one step and in limited time, it
has also given a zero value of a number of network connections, such as
some connections related of relative humidity input because of the lake
of impact this parameter on the runoff when other parameters are
avaliable.
This study recommend to use this technique in forecasting of
evaporation and other climatic elements.
References used
AWAD, A. ؛POSER, I. 2007-Calibrating Conceptual Rainfall- Runoff Models Using a Real Genetic Algorithm Combined with a Local Search Method, Vol. 1, 174-181
Mutlu, E; Chaubey, I; Hexmoor, H; Bajwa, S. 2008- Comparison of artificial neural network models for hydrologic predictions at multiple gauging stations in an agricultural watershed, Published online in Wiley InterScience, 1-10
ASADI, S.؛ SHAHRABI, J.؛ ABBASZADEH, P. ؛TABANMEHR, S. 2013- A new hybrid artificial neural networks for rainfall_runoff process modeling, Neurocomputing an international journal, Iran, 470_480
The relationship between precipitation and surface runoff is one of
the fundamental components of the hydrological cycle of water in
nature and is one of the most complex and difficult to understand
because of the large number of parameters involv
The relation between rainfall and runoff forms one of the main hydrological cycle elements. It is one of the most complex hydrological phenomena because of the great numbers of parameters used in modeling the physical processes, the expansion of thei
In this research, a hybrid system was proposed between the
genetic algorithm and the fuzzy Kohonen clustering network ,
where the genetic algorithm is one of the methods of artificial
intelligence is one of the modern methods.
the aim of this study is
determination of the most influential climatic factors in the rainfall
runoff relationship in Al-Kabir Al-shimalee river using artificial
neural networks. The inputs included Precipitation, runoff, in
different delays, in
The principal objective of this research is an adoption of the Genetic
Algorithm (GA) for studying it firstly, and to stop over the operations which
are introduced from the genetic algorithm.The candidate field for applying
the operations of the g