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Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very good startup to establish a rule of thumb in the laboratories to compare between observations. The importance of linear regression equations in predicting surface water quality parameters is a method that can be applied to any other location.  

Crossref
Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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Crossref
Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Detecting Outliers In Multiple Linear Regression
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It is well-known that the existence of outliers in the data will adversely affect the efficiency of estimation and results of the current study. In this paper four methods will be studied to detect outliers for the multiple linear regression model in two cases :  first, in real data; and secondly,  after adding the outliers to data and the attempt to detect it. The study is conducted for samples with different sizes, and uses three measures for  comparing between these methods . These three measures are : the mask, dumping and standard error of the estimate.

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Crossref
Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Proposed method to estimate missing values in Non - Parametric multiple regression model
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In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

 

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Crossref
Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Robust estimation of multiple linear regression parameters in the presence of a problem of heterogeneity of variance and outliers values
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Often times, especially in practical applications, it is difficult to obtain data that is not tainted by a problem that may be related to the inconsistency of the variance of error or any other problem that impedes the use of the usual methods represented by the method of the ordinary least squares (OLS), To find the capabilities of the features of the multiple linear models, This is why many statisticians resort to the use of estimates by immune methods Especially with the presence of outliers, as well as the problem of error Variance instability, Two methods of horsepower were adopted, they are the robust weighted least square(RWLS)& the two-step robust weighted least square method(TSRWLS), and their performance was verifie

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Crossref
Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Estimate Raw Water Salinity for the Tigris River for a Long Time Using a Mathematical Model
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Abstract<p>The measurement data of the raw water quality of Tigris River were statistically analyzed to measure the salinity value in relation to the selected raw water quality parameters. The analyzed data were collected from five water treatment plants (WTPs) assembled alongside of the Tigris River in Baghdad: Al-Karkh, Al-Karama, Al-Qadisiya, Al-Dora, and Al-Wihda for the period from 2015 to 2021. The selected parameters are total dissolved solid (TDS), electrical conductivity (EC), pH and temperature. The main objective of this research is to predicate a mathematical model using SPSS software to calculate the value of salinity along the river, in addition, the effect of electrical conductivi</p> ... Show More
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Publication Date
Wed Jul 29 2020
Journal Name
Iraqi Journal Of Science
Use of Two Aquatic Snail Species as Bioindicators of Heavy Metals in Tigris River-Baghdad
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     Thirty individuals of Bellamya bengalensis and Physella acuta were collected and identified from the Tigris River in Baghdad during the period between October to November 2017. The efficiency of bioaccumulation of the two species as bioindicators for aquatic heavy metal pollution with Cd, Ni, Pb and Cu was investigated. Both snail species had the ability to accumulate heavy metals. The mean of Ni concentration in soft tissues of both snails was 1.53 ppm while the mean concentration of other heavy metals was significantly lower; they reached 0.51 ppm, 0.36 ppm and 0.29 ppm, respectively. While no significant differences between B. bengalensis and  P.acuta were noticed in th

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
The Limnological Effects of River Lesser-Zab on Tigris River, Iraq
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The present study included the physico-chemical parameters of Lesser-Zab river and its effects on Tigris river. Monthly water samples were taken from the two rivers during January to October 1999.There were no signifcant difference in water temperatures. Both rivers were fresh to oligohalin, alkaline and very hard. Close values were determined in total suspended solids in both rivers with little increasing during rainfall period and high discharge. Water was well areated and over saturation was recorded in several occasions. Dissolved oxygen values of Tigris river were influenced by Lesser-Zab. Cations were more dominant than anions in both rivers. In Lesser-Zab, the anions were increased during spring season and declined in summer which t

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Crossref
Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
The Effect of Tharthar-Tigris Canal on the Environmental Properties of the Tigris River Northern Baghdad, Iraq
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The present study is considered the first on this sector of the Tigris River after 2003. It is designed for two aims, the first is to demonstrate the seasonal variations in physicochemical parameters of Tharthar-Tigris Canal and Tigris River; the second is to explain the possible effects of canal on some environmental properties in the Tigris River. Water samples were being collected monthly. Six sampling sites were selected, two on Tharthar Canal and four along the Tigris River, one before the confluence as a control site and the others downstream the confluence with the canal. For a period from January to December 2020, nineteen physicochemical parameters were investigated including air and water temperature, turbidity, electrical cond

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