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A comparative study of adaptive neuro fuzzy inference system and artificial neural networks for predicting groundwater hydraulic head in an arid region
Other Title(s)
دراسة مقارنة لنظام الاستدلال العصبي الضبابي المكيف و الشبكات العصبية الاصطناعية للتنبؤ بالمنسوب الهيدروليكي للمياه الجوفية في منطقة قاحلة
Joint Authors
Hasan, Ayman Alak
Munshid, Huda Faysal
al-Ubaydi, Ali Hasan Razzuqi
Source
Journal of University of Babylon for Engineering Sciences
Issue
Vol. 27, Issue 4 (31 Dec. 2019), pp.317-328, 12 p.
Publisher
Publication Date
2019-12-31
Country of Publication
Iraq
No. of Pages
12
Main Subjects
Abstract EN
The aim of this research is to develop a predictive model to estimate the groundwater head in Safwan-Zubair area by using an adaptive neural fuzzy inference system (ANFIS).
This area represents the southern sector of the Iraqi Desert, an arid region with scarce and limited resources.
The data required for building the ANFIS model are generated using MODFLOW model (V.5.3).
MODFLOW model was calibrated based on field measurements during one year.
MODFLOW model generated (3797) hydraulic head values during each month.
70% of these values (2658 samples) was used for training, 30% of these values (1139 samples) was used for checking.
The accuracy of the ANFIS models are compared with previous work based on artificial neural network (ANN) technique.
Different combination of successive hydraulic heads and recharge rates of groundwater is used as input variables.
There is no significant increase in the estimation accuracy when adding another input variable (recharge rate).
Because the amount of this variable is very little, so its influence on the results was imperceptible.
A comparison of ANFIS and ANN shows that the ANFIS model performs preferable than the ANN model on the checking phase.
ANFIS model combines both fuzzy logic basics and neural networks; thus their properties can be utilized in one frame.
It can be concluded, the ANFIS model appears to be more convenient than the ANN model for predicting groundwater hydraulic head from related input data.
American Psychological Association (APA)
al-Ubaydi, Ali Hasan Razzuqi& Hasan, Ayman Alak& Munshid, Huda Faysal. 2019. A comparative study of adaptive neuro fuzzy inference system and artificial neural networks for predicting groundwater hydraulic head in an arid region. Journal of University of Babylon for Engineering Sciences،Vol. 27, no. 4, pp.317-328.
https://search.emarefa.net/detail/BIM-950028
Modern Language Association (MLA)
al-Ubaydi, Ali Hasan Razzuqi…[et al.]. A comparative study of adaptive neuro fuzzy inference system and artificial neural networks for predicting groundwater hydraulic head in an arid region. Journal of University of Babylon for Engineering Sciences Vol. 27, no. 4 (2019), pp.317-328.
https://search.emarefa.net/detail/BIM-950028
American Medical Association (AMA)
al-Ubaydi, Ali Hasan Razzuqi& Hasan, Ayman Alak& Munshid, Huda Faysal. A comparative study of adaptive neuro fuzzy inference system and artificial neural networks for predicting groundwater hydraulic head in an arid region. Journal of University of Babylon for Engineering Sciences. 2019. Vol. 27, no. 4, pp.317-328.
https://search.emarefa.net/detail/BIM-950028
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 325-327
Record ID
BIM-950028