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Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
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The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. The artificial neural networks show a high coefficient of determination between the predicted and observed domestic solid waste, with R2 value reaching to 0.91, 0.828 and 0.827 for Al-Karkh, 0.9986,0. 9903 and 0.9903 for Rusafa side, and 0.9989, 0.9878 and 0.9847 in Baghdad city, and also, these models were used to estimate the generation of municipal solid waste for short period with highly efficient which assistance in planning to design landfills sites.

 

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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Study Impact of Some Factors on Daily Number of Hours Providing of Electricity in Baghdad City Using Path Analysis
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دُرِست العوامل المؤثرة في عدد ساعات تجهيز الكهرباء في مدينة بغداد، وتكونت عينة الدراسة من (365) مشاهدة يومية لعام 2018، وتمثلت بستة متغيرات استعملت في الدراسة. كان الهدف الرئيس هو دراسة العلاقة بين هذه المتغيرات، وتقدير تأثيرات المتغيرات التنبؤية في المتغير التابع (عدد ساعات تجهيز الكهرباء في مدينة بغداد). ولتحقيق ذلك استعملت نمذجة المعادلات الهيكلية/ تحليل المسار وبرنامج AMOS

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Publication Date
Wed Jan 01 2014
Journal Name
International Journal Of Computer Applications
Enhancing the Delta Training Rule for a Single Layer Feedforward Heteroassociative Memory Neural Network
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In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories &amp; Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Compared with Genetic Algorithm Fast – MCD – Nested Extension and Neural Network Multilayer Back propagation
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The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MEASUREMENT OF GROUND LEVEL OZONE IN SELECTIVE LOCATIONS IN BAGHDAD CITY
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The ground level ozone concentration at different locations in Baghdad city was identified. Five
different sites have been chosen to identify the ground level ozone concentration. Al- Dora and Al-
Za'afarania were chosen as areas contained point source ( power plant station ) in addition to high traffic
load , while Al –Uma park, Aden square and Al-Mawal square were chosen as area contained heavy
traffic only (line source). The measurement focuses on spring and fall because these periods display
favorable meteorology to ozone formation. During the research period the maximum values (peaks) for
ground level ozone concentration were observed at fall: at Al-Za'afarania area 101ppb as an average, at
Al-Dora 87 ppb as a

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Publication Date
Tue Feb 01 2022
Journal Name
Biochemical & Cellular Archives,
BACTERIAL CONTAMINATION OF IRAQI BANKNOTES CURRENCY IN CIRCULATION IN BAGHDAD CITY
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The present study was identified the type of bacterial contamination of Iraqi banknotes currency (Iraqi dinars) in circulation. 68 Iraqi banknotes currency of different denominations samples were randomly gathered from different locations and different occupational groups in Baghdad city. The results showed 61 (89.70%) of the samples were determined to be contaminated with bacteria, whereas 7 (10.29%) were confirmed to be sterile. A total of 11 different species of bacteria resulting in 72 isolates were found from those 61 contaminated Iraqi banknotes currency. Based on culture, morphological and biochemical tests, 11 isolates were identified as Bacillus sp., Staphylococcus aureus, Staphylococcus epidermidis, Corynebacterium diphtheria, Leu

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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
5 year-analysis of reported dog bites in Baghdad city
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Background: Animal bites in humans are an important public health problem. Most of these bites are dog bites. Dog bites in humans are a complex problem embracing public health and animal welfare, both in developed and developing nations. .
Al-kindy Col Med J Vol.8 No.2 2012 P: 149
Objectives: in order to estimate the magnitude of the problem and to understand the epidemiological characteristics of dog bite victims registered in Baghdad city regarding their age, sex, number of registered dog bite victims per month and year along the studied period ( 2006-2010) and also to sniff out any seasonal variation in dog bite attacks .
Methods: A across-sectional study was carried out during January (2011), in the Anti-Rabies clinic of (Pa

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Publication Date
Sun Dec 30 2012
Journal Name
Al-kindy College Medical Journal
5 year-analysis of reported dog bites in Baghdad city
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Background: Animal bites in humans are an important public health problem. Most of these bites are dog bites. Dog bites in humans are a complex problem embracing public health and animal welfare, both in developed and developing nations. .
Al-kindy Col Med J Vol.8 No.2 2012 P: 151
Objectives: in order to estimate the magnitude of the problem and to understand the epidemiological characteristics of dog bite victims registered in Baghdad city regarding their age, sex, number of registered dog bite victims per month and year along the studied period ( 2006-2010) and also to sniff out any seasonal variation in dog bite attacks .
Methods: A across-sectional study was carried out during January (2011), in the Anti-Rabies clinic of (Pa

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Publication Date
Sun Oct 29 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Premenstrual Syndrome among Working Women in Baghdad City
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Objectives: To assess the premenstrual syndrome among the working women in Baghdad City.
Methodology: A cross-sectional analytic study, using probability sampling cluster (multi-stage) sampling of
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designed and consisted of (4) parts, including demographic, reproductive, menstrual cycle characteristics, and
premeustmual syndrome symptoms. Content validity and reliability of the questionnaire were detemined by
conducting a pilot study. Descriptive and inferential statistical procedures were used to analyze the data.
Results: The results of the study revealed that the age of women ranged betwee

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