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Bayesian methodology for spatial quantile autoregressive model estimation
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Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data problems caused by outliers. A simulation study was conducted using the Monte Carlo method, which is used to generate data according to the distribution and resample until the parameters of the used method converge. The Bayesian method was employed to estimate the model parameters due to its ability to achieve accurate parameter estimates and overcome the challenges faced by traditional estimation methods in this model. The results confirmed the importance of considering spatial aspects when analyzing data, as they significantly impact the model's accuracy. The simulation study was carried out using R software.

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Revolution In Science And Humanity
Nonparametric Estimation of Failure Periods for Log Normal Distribution Using Bootstra
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A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

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Publication Date
Mon Apr 03 2023
Journal Name
Karbala International Journal Of Modern Science
Performance Estimation and System Modeling for Refractive Index Structure Constant Cn2
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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Compared Some Estimators Ordinary Ridge Regression And Bayesian Ridge Regression With Practical Application
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Maulticollinearity is a problem that always occurs when two or more predictor variables are correlated with each other. consist of the breach of one basic assumptions of the ordinary least squares method with biased estimates results, There are several methods which are proposed to handle this problem including the  method To address a problem  and  method To address a problem , In this research a comparisons are employed between the biased   method and unbiased   method with Bayesian   using Gamma distribution  method  addition to Ordinary Least Square metho

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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
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Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
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Publication Date
Thu Dec 21 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Enhancing Spatial Accuracy of OpenStreetMap Data: A Geometric Approach
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OpenStreetMap (OSM), recognised for its current and readily accessible spatial database, frequently serves regions lacking precise data at the necessary granularity. Global collaboration among OSM contributors presents challenges to data quality and uniformity, exacerbated by the sheer volume of input and indistinct data annotation protocols. This study presents a methodological improvement in the spatial accuracy of OSM datasets centred over Baghdad, Iraq, utilising data derived from OSM services and satellite imagery. An analytical focus was placed on two geometric correction methods: a two-dimensional polynomial affine transformation and a two-dimensional polynomial conformal transformation. The former involves twelve coefficients for ad

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Publication Date
Wed Oct 26 2022
Journal Name
Iraqi Journal Of Science
Gene Expression Analysis via Spatial Clustering and Evaluation Indexing
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The density-based spatial clustering for applications with noise (DBSCAN) is one of the most popular applications of clustering in data mining, and it is used to identify useful patterns and interesting distributions in the underlying data. Aggregation methods for classifying nonlinear aggregated data. In particular, DNA methylations, gene expression. That show the differentially skewed by distance sites and grouped nonlinearly by cancer daisies and the change Situations for gene excretion on it. Under these conditions, DBSCAN is expected to have a desirable clustering feature i that can be used to show the results of the changes. This research reviews the DBSCAN and compares its performance with other algorithms, such as the tradit

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Publication Date
Fri May 15 2009
Journal Name
Journal Of Planner And Development
Spatial Disparities of Primary Education Services in Sulaimaniyah Province
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Levels of primary education are varying in Sulaimaniyah Province, which defines as a lower stage of education process and seems to be found in most settlements to save the individual and community from illiteracy in its traditional notion which means the individuals, potentiality for reading and writing if he/she graduated from this stage successfully. The research can put the priority for goodness of primary education service within Sulaimaniyah Province that includes Sulaimaniyah city as a dominance based on statistical indicator which called the standardized score (z). The indicator (z) calculated for the basic items of primary education to diagnosis the range of developing that service in Sulaimaniyah city especially and put

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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
Tue Jun 01 2021
Journal Name
Journal Of Planner And Development
The Importance of Spatial Indicators to Producing Development Plans
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  The indicators were important core for any work, and may be occurring this indicators way of communicating among planers and decision makers, even also for public participating, do make any decision. The urban and regional planning is one of those science highly depending on using indictors, for two  reasons, first, way to communicating ideas between specialist and non-specialist, (politician and decision makers), the second one, this field are multidisciplinary science, so the need indictors to clearing thoughts among different backgrounds in one team, as common language.

This research tries to clear importance of GIS in forming and building Spatial Planning Indicators, to cross communication problem among planning g

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Artificial Intelligence Based Deep Bayesian Neural Network (DBNN) Toward Personalized Treatment of Leukemia with Stem Cells
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

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