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Comparison between Linear and Non-linear ANN Models for Predicting Water Quality Parameters at Tigris River
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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( ), Phosphate,( ) Sulfate(), Nitrate( ), 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%).

 

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison of Parameters Estimation Methods for the Negative Binomial Regression Model under Multicollinearity Problem by Using Simulation
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This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

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Publication Date
Thu Jun 29 2023
Journal Name
Wasit Journal For Pure Sciences
Association between Anthropometric Measurements and some Biochemical Parameters in Premenopausal and Postmenopausal Women
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Numerous physiological and biochemical changes are linked to menopause. The current study was intended to examine the transforms linked to anthropometric measurements and bone-related factors. In this study of 80 women which included; they comprised 40 premenopausal women and 40 postmenopausal women. waist circumference (WC), body mass index (BMI), hip circumference (HC), moreover waist to hip ratio are among the anthropometric measurements (W-HR) recorded by standard procedures. The plasma samples were tested for the following biochemical parameters: bone-related parameters [calcium (Ca), phosphorus (P), uric acid (UA), alkaline phosphatase (ALP), and erythrocyte sedimentation rate (ESR)] and serological agglutination tests [rheumat

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Publication Date
Sat Feb 27 2021
Journal Name
Journal Of Engineering
Using Geographic Information Systems (GIS) Program and Water Quality Index (WQI) to Assess and Manage Groundwater Quality in the City of Baghdad
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Groundwater is an essential source because of its high quality and continuous availability characterize this water resource. Therefore, the study of groundwater has required more attention. The present study aims to assess and manage groundwater quality's suitability for various purposes through the Geographical Information System GIS and the Water Quality Index WQI. The study area is located in the city of Baghdad in central Iraq, with an approximate area of ​​900 , data were collected from the relevant official departments representing the locations of 97 wells of groundwater in the study area for the year 2019, as it included physicochemical parameters such as  pH, EC, TDS, Na, K, Mg, Ca, Cl,  , and &nbs

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of estimations methods of the entropy function to the random coefficients for two models: the general regression and swamy of the panel data
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In this study, we focused on the random coefficient estimation of the general regression and Swamy models of panel data. By using this type of data, the data give a better chance of obtaining a better method and better indicators. Entropy's methods have been used to estimate random coefficients for the general regression and Swamy of the panel data which were presented in two ways: the first represents the maximum dual Entropy and the second is general maximum Entropy in which a comparison between them have been done by using simulation to choose the optimal methods.

The results have been compared by using mean squares error and mean absolute percentage error to different cases in term of correlation valu

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Publication Date
Wed Jul 01 2020
Journal Name
Proceedings Of The Institution Of Mechanical Engineers, Part H: Journal Of Engineering In Medicine
Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury
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Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

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Publication Date
Sat Jan 09 2016
Journal Name
World Journal Of Experimental Biosciences
Comparative study of oral bacterial composition and neutrophil count between smokers and non-smokers
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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Computers, Communications, Control And Systems Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of Engineering
Improving Water Use Efficiency and Water Productivity for Okra Crop by using Subsurface Water Retention Technology
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Utilizing the modern technologies in agriculture such as subsurface water retention techniques were developed to improve water storage capacities in the root zone depth. Moreover, this technique was maximizing the reduction in irrigation losses and increasing the water use efficiency. In this paper, a polyethylene membrane was installed within the root zone of okra crop through the spring growing season 2017 inside the greenhouse to improve water use efficiency and water productivity of okra crop. The research work was conducted in the field located in the north of Babylon Governorate in Sadat Al Hindiya Township seventy-eight kilometers from Baghdad city. Three treatments plots were used for the comparison using surface

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Publication Date
Mon Jan 01 2018
Journal Name
Biochemical And Cellular Archive
Irrigation intervals affect dhn1 expression and some physiological parameters in stay green and non-stay-green sorghum
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