Comparison between linear and non-linear ANN models for predicting water quality parameters at Tigris River
Other Title(s)
المقارنة بين نموذج الشبكة العصبية الاصطناعية ذو المدخلات الخطية و اللاخطية لتخمين معاملات نوعية المياه في نهر دجلة
Joint Authors
al-Suhaili, Rafi Hashim Shakir
Muhammad, Zaynab Jabir
Source
Issue
Vol. 20, Issue 10 (31 Oct. 2014), pp.1-15, 15 p.
Publisher
University of Baghdad College of Engineering
Publication Date
2014-10-31
Country of Publication
Iraq
No. of Pages
15
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Topics
Abstract AR
في هذا البحث طبقت تقنية الشبكات العصبية الاصطناعية (ANNs) في محاولة لتخمين مستويات المياه و البعض من معايير نوعية المياه في نهر دجلة في محافظة واسط لخمسة مواقع مختلفة.
هذه التخمينات مفيدة في التخطيط و الإدارة و تقييم مصادر المياه في المنطقة.
أن البيانات المكانية على طول النظام نهري أو مواقع المنطقة المختلفة في المنطقة لها قياسات مفقود عادة، لذلك فأن من الضروري بناء نموذج تخمين دقيق لمليء هذه القيم المفقودة.
Abstract EN
In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites.
These predictions are useful in the planning, management, evaluation of the water resources in the area.
Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction.
model to fill these missing values is essential. The selected sites for water quality data prediction were Sewera, Numania , Kut u / s, Kut d / s, Garaf observation sites.
In these five sites models were built for prediction of the water level and water quality parameters.
the following (Biological Oxygen Demand (BOD5), Phosphate, (PO4) Sulfate (SO4), Nitrate (NO3), Calcium (Ca), Magnesium (Mg), Total Hardness (TH), Potassium (K), Sodium (Na), Chloride (CL), Total Dissolved Solids (TDS), Electric conductivity (EC), Alkalinity (ALK)). The ANN models tried herein were the Multisite-Multivariate ANN models (5-sites, 14 variables), five models were built, one for each of the five stations as the missing data station.
The linear ANN (traditional) models fail to make the prediction of all variables with high correlation coefficient simultaneously.
Hence a non-linear input ANN model was developed herein and believed to be a new modification in ANN modeling.
It was found that the ANNs have the ability to predict water level and water quality parameters at all the sites with a good degree of accuracy, the range of correlation coefficients obtained are (12.9 %-97.2 %) for linear models, while for this model with Non-linear terms, The range of correlation coefficients obtained is (71.8 %-99.6 %).
American Psychological Association (APA)
al-Suhaili, Rafi Hashim Shakir& Muhammad, Zaynab Jabir. 2014. Comparison between linear and non-linear ANN models for predicting water quality parameters at Tigris River. Journal of Engineering،Vol. 20, no. 10, pp.1-15.
https://search.emarefa.net/detail/BIM-409022
Modern Language Association (MLA)
al-Suhaili, Rafi Hashim Shakir& Muhammad, Zaynab Jabir. Comparison between linear and non-linear ANN models for predicting water quality parameters at Tigris River. Journal of Engineering Vol. 20, no. 10 (Oct. 2014), pp.1-15.
https://search.emarefa.net/detail/BIM-409022
American Medical Association (AMA)
al-Suhaili, Rafi Hashim Shakir& Muhammad, Zaynab Jabir. Comparison between linear and non-linear ANN models for predicting water quality parameters at Tigris River. Journal of Engineering. 2014. Vol. 20, no. 10, pp.1-15.
https://search.emarefa.net/detail/BIM-409022
Data Type
Journal Articles
Language
English
Notes
Includes appendices : p. 9-15
Record ID
BIM-409022