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ijp-1015
Development and Assessment of Feed Forward Back Propagation Neural Network Models to Predict Sunshine Duration
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         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmospheric pressure were used as input parameters in order to obtain the daily average of sunshine duration (SD) as the output. The eight-year data were divided into two categories. The first category covers whole years (annually) and the second category is seasonal. To recognize and assess the influence of different input parameters on sunshine duration, six models of ANN have been evolved. The findings showed that in the annual models, the outcomes of RMSE, MAE and R for the model with input parameters (Month, Cloud Level and Average Temperature) were the best results 1.82, 1.175 and 0.89, respectively. As for the season models, the outcomes of RMSE, MAE and R for the autumn season were the best results 1.450, 1.009 and 0.94, respectively. Accordingly, the performance of the artificial neural network is considerably effective in predicting the sunshine duration.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Quantitative and qualitative assessment of the basic components and effective in Acol plant
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Key components estimated in Acol total plant leaves and the results were as follows plant Acol humidity 72%

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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Publication Date
Wed May 01 2013
Journal Name
Journal Of Computer Science
PROTOCOLS FOR SECURE ROUTING AND TRANSMISSION IN MOBILE AD HOC NETWORK: A REVIEW
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Mobile ad hoc network security is a new area for research that it has been faced many difficulties to implement. These difficulties are due to the absence of central authentication server, the dynamically movement of the nodes (mobility), limited capacity of the wireless medium and the various types of vulnerability attacks. All these factor combine to make mobile ad hoc a great challenge to the researcher. Mobile ad hoc has been used in different applications networks range from military operations and emergency disaster relief to community networking and interaction among meeting attendees or students during a lecture. In these and other ad hoc networking applications, security in the routing protocol is necessary to protect against malic

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Publication Date
Mon Dec 19 2022
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of NursesPractice Regarding Poisoning Children
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Assessment of Modified - Asphalt Cement Properties
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The Asphalt cement is produced as a by-product from the oil industry; the asphalt must practice further processing to control the percentage of its different ingredients so that it will be suitable for paving process. The objective of this work is to prepare different types of modified Asphalt cement using locally available additives, and subjecting the prepared modified Asphalt cement to testing procedures usually adopted for Asphalt cement, and compare the test results with the specification requirements for the modified Asphalt cement to fulfill the paving process requirements. An attempt was made to prepare the modified Asphalt cement for pavement construction in the laboratory by digesting each of the two penetration grade Asphalt c

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Publication Date
Thu Dec 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Clinicopathological assessment of chronic hyperplastic candidasis
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Background: Chronic hyperplastic candidiasis is the least common type of oral candidiasis. The diagnosis, long-term treatment, and prognosis of this potentially malignant oral condition are still currently unclear. Objective: the aim of this study is to analyze the demographic features and clinical characteristics of oral chronic hyperplastic candidiasis. Materials and Methods: A retrospective analysis was performed on blocks and case sheets of patients who were diagnosed with chronic hyperplastic candidiasis in the archives of Oral and Maxillofacial Pathology at the College of Dentistry/University of Baghdad. Demographic and clinical characteristics were analyzed. Results: twenty-one cases with chronic hyperplastic candidiasis were coll

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Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Risk-health Related Behaviors of Female Adolescents and Their Determinants
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Objectives: The study aims to assess the female adolescents’ risk-health behaviors, to identify their
determinants, to determine the association between the risk health behaviors and the stage of
adolescence for these females' demographic variable.
Methodology: A purposive sample of (268) female adolescents is selected from intermediate and
secondary schools in Baghdad City. These adolescents have presented the age of (14-19) year old and
divided into two groups of (14-16) year and (17-19) year. A questionnaire is constructed for the purpose
of the study, it is composed of (10) major parts, and the overall items, which are included in the
questionnaire, are (106) item. Reliability and validity of the questionnaire

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Publication Date
Tue Jan 01 2019
Journal Name
World Journal Of Dentistry
Assessment of Implant Stability Changes and Success Rate of Narrow Dental Implants
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Aims: To assess the success rate and implant stability changes of narrow dental implants (NDIs) during the osseous healing period. Materials and methods: This prospective observational clinical study included 21 patients with narrow alveolar ridge of restricted mesiodistal interdental span who received NDIs. The alveolar ridge width was determined by the ridge mapping technique. Implant stability was measured using Periotest® M immediately after implant insertion then after 4 weeks, 8 weeks and 12 weeks postoperatively. The outcome variables were success rate and implant stability changes during the healing period. The statistical analysis included one-way analysis of variance (ANOVA) and Tukey\'s multiple comparisons test, values < 0.05 w

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering Science And Technology
Quantitative and qualitative assessment of groundwater: The case of Khanaqin alluvial (Iraq
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Scopus (4)
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