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joe-2034
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
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ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data set sub-division into training, testing and holdout data sub-sets, and different number of hidden nodes in the hidden layer. It is found that it is not necessary that the nearest station to the station under prediction has the highest effect; this may be attributed to the high differences in elevation between the stations. It can also found that the variance is not necessary has effect on the correlation coefficient obtained.

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Estimation Multivariate data points in spatial statistics with application
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This paper  deals  to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th

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Publication Date
Wed Jun 20 2018
Journal Name
Al-academy
Spatial transformations and visual construction in the contemporary theater
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The current research deals with the subject of spatial transformations and visual construction in contemporary theater. How the visual system works to create spatial diversity in the contemporary Iraqi theater performance and how visual construction contributes to a spatial development process capable of building a tourism system that creates an architectural architecture that leaves the topography of the scriptural architecture. And the production of various indications and patterns in the scene of theatrical presentation in order to produce the new foundational meaning by creating a new structure that leads to diversity and diversity in the visual system and the beginning of visual constructions and their applications. Knowledge and te

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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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Publication Date
Sat Dec 21 2024
Journal Name
Edelweiss Applied Science And Technology
Using count regression models to investigate the most important economic factors affecting divorce in Iraq
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The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Measurement of Indoor Radon Gas Concentration in same Region of Baghdad Governorate Using CR-39 Nuclear Track Detector
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In this research the activity of radon gas in air in Baghad governorate,Iraq, using “alpha-emitters track registration (CR-39) track detector were measured. This measurement was done for selected areas from Baghdad Governorate, The results obtained shows that the highest average concentrations for Rn-222 is (179.077 Bq/m^3) which was recorded within Al-Shaaib city and less average concentrations was (15.79 Bq/m^3) in the nearby residential area of Baghdad International Airport and the overall average concentrations is (86.508 Bq/m^3) for these regions. Then the radon concentration was measured annual effective dose calculated from radon concentration and found in range from 0.4031 mSv/y to 4.5179 mSv /y with an average value of 2.1824 m

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Publication Date
Wed Nov 07 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Measles in Kirkuk Governorate: Cohort Study
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Objective(s): To describe the demographic attributes, vaccination status of measles patients and the occurrence of
the disease according to time and place in Kirkuk governorate during the year 2010.
Methodology: The epidemiological study (a descriptive study) on measles cases was carried out in Kirkuk province
which is one of the Iraqi governorates from January 20th to July 30th, 2011. Data were collected retrospectively by
review of patients' files that were registered at the department of statistic in health directorate of Kirkuk during the
year 2010. A purposive "non-probability" sample of (152) confirmed measles cases (clinically and laboratory) that
were registered at the department of statistic in health directora

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Publication Date
Wed Mar 20 2019
Journal Name
International Journal Of Research In Social Sciences And Humanities
THE WATER ECOSYSTEM OF THE MARSHES OF MAYSAN GOVERNORATE USING REMOTE SENSING AND GIS
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The study addressed the water ecosystems of the marshes of Maysan Governorate as one of the important areas in Iraq in terms of the environmental, economic and tourism aspects. This area was exposed to great environmental changes due to natural and human factors which greatly affected the water ecosystem and made the area susceptible to many problems that affected the biological life of living organisms. The marshes of Maysan Governorate was affected by vital factors and non-vital factors. The marshes of Maysan Governorate was characterized by the UN Organization as one of the most important centers of biodiversity in the world because of the abundance of different and rare living organisms such as birds, fish, and reptiles as well as the e

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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparison between the estimated of nonparametric methods by using the methodology of quantile regression models
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This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Relationship between Renal Function Tests and the Levels of MDA, Zinc, and Cadmium among Painters in Sulaimani
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Kidney damage in workers within environments of highly expected exposure to toxin, including heavy metals, could be a primary marker to expect hazards in population exposed to low levels of many environmental pollutants. The present study was designed to evaluate the possible effect of environmental exposure to cadmium and zinc on renal function among painters in Sulaimani city. Cross sectional study was performed on 37 male painting workers in Sulaimani city. Each worker was interviewed using structured questionnaire. Twenty five non-exposed healthy subjects were included as control group. Venous blood samples (10 ml) were obtained by vein puncture from both subjects and utilized for estimation of serum urea, creatinine levels, serum le

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Publication Date
Sun Nov 01 2020
Journal Name
International Journal Of Engineering
Pavement Maintenance Management Using Multi-objective Optimization: (Case Study: Wasit Governorate-Iraq)
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