The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge have the most significant affect on the predicted TDS concentrations. The results showed that a network with (8) hidden neurons was highly accurate in predicting TDS concentration. The correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE) between measured data and model outputs were calculated as 0.975, 113.9 and 11.51%, respectively for testing data sets. Comparisons between final results of ANNs and multiple linear regressions (MLR) showed that the ANNs model could be successfully applied and provides high accuracy to predict TDS concentrations as a water quality parameter.
The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A
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A total of 109 fish specimens belonging to six species (Barbus grypus, B. luteus, B. xanthopterus, Cyprinion macrostomum, Cyprinus carpio and Liza abu) were collected from Tigris river passing through Salah Al-Deen province during the period from September 2008 till January 2009. These fishes were infected with nine parasite species which included two sporozoans (Myxobolus mülleri and Dermocystidium percae), three ciliates (Trichodina cottidarum, T. elegini and T. murmanica) and four monogenetic trematodes (Dactylogyrus rhodeianus, D. vastator, Paradiplozoon cyprini and Microcotyle donavini). Among these parasites, two trichodinids (T. elegini and T. murmanica) were reported for the first time from fishes of Iraq. Also, B. grypus is c
... Show MoreThis study describes the determination of some phenols in four different zones of Tigris river in Iraq including, AL-Krieat, AL-Kadhimiya, AL-Jadiriyah, and AL-Adhamiyah. The phenolic compounds analyzed were (2,3-dimethylphenol, 4-chlorophenol, 3-nitrophenol and 2,4-dinitrophenol) using reverse phase high performance liquid chromatography (RPHPLC) with a UV detector on ODS-C18 column(150×4.6 mm I.D) and a mobile phase consisted of methanol-water(30:70)%(v/v) at pH 5.0, and a column temperature at 30C° with 20 µL injection. UV detection helps to identify different phenols at wave length at 280 nm with a flow rate at 0.5 ml/min. The separation time was (< 6) min.The results indicated that the AL-Adhami
... Show MoreThere is a scarcity of data regarding algal flora of Tigris River in the territory of Baghdad. The present study deals with Tigris River in Al-Dora site in Baghdad province from November 2014 to June 2015 in order to shed light on its epiphytic Algae on (Phragmites australis) and epipelic algae. An amount of 183 and 154 species of epiphytic and epipelic algae are identified respectfully. The Bacillariophyceae (diatoms) are the dominant algal group followed by Cyanophyceae and Chlorophyceae. Moreover, 90 species are shared between two groups of algae (epiphytic and epipelic) and identified at the study site. Additionally, the seasonal variations and diversity of algal species are noticed. The highest number of epiphytic algae is 772.05 x 104
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This study aims to predict the organic pollution produced from the presence of some polycyclic aromatic hydrocarbons (PAHs) and determination it's concentrations (µg/L , ppb) in Tigris river water by a collection twenty-seven water samples from a selected three stations with nine sampling sites and three depths of water (5 cm , 2 m and 4 m) each site for 4.6 km distance of a geographic studied area which is located between the ( Al-Senak and AL-Sarrafiah bridges ) at Baghdad city – Iraq on May, 2012. The geographic location was determined with a Global Positioning System (GPS) and Geographic Information System (GIS) software program. The concentrations of fourteen components (PAHs) were performed using the reverse phase
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In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.
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