Volume 22 Issue 2
Published: 2025-12-01
Contents
Article
Comparison of Wavelet Shrinkage and Hampel Filter in the Analysis of Multivariate Linear Regression Models
Amira Wali Omer, Taha Hussein Ali
The presence of outliers in the data of a multivariate regression model affects the accuracy of the estimated model parameters and leads to unacceptably large residual values. Therefore, some...
DOI: 10.33899/iqjoss.v22i2.54068
Using Deep learning and GIS applications to Extract Features from Remote Sensing Data
Faten Azeez Mustafa
In recent years, artificial intelligence (AI) has advanced quickly, equal or perhaps even outperforming human accuracy in tasks like picture recognition, reading comprehension, and text...
DOI: 10.33899/iqjoss.v22i2.54069
Diagnosis and Classification of Alzheimer's Disease Using Some Machine Learning Models: A Comparative Study
Saman Hussein Mahmood
Alzheimer's disease damages brain neurons, resulting in memory loss. Early and accurate diagnosis of the disease is crucial for implementing preventive measures. However, differentiating between...
DOI: 10.33899/iqjoss.v22i2.54070
Estimating the Population Mean in Stratified Median ranked Set Sampling Using Combined and Separate Regression with the Presence of Outliers
Ayman M. AL-Hadidi, Rikan A. Ahmed
This research aims to demonstrate the high efficiency and accuracy in estimating the limited population mean through the estimates of the separate and combined stratified regression line based...
DOI: 10.33899/iqjoss.v22i2.54071
A Multi-Objective Optimization Approach for Design Earth-Fill Dams Variables
Goran H. Abdalla, Ayad M. Ramadan, Nazim Abdul Nariman
The entire research study is about the optimization of design variables for an earth-fill dam utilizing multi-objective optimization approach. We have considered three variables that are related...
DOI: 10.33899/iqjoss.v22i2.54072
Diagnosing Cross-Sectional Time Series Models of Money Supply For Arab Countries
Yousif Ahmed Khalaf, Najlaa Saad Ibrahim
Using cross-sectional time series models, the study concludes by determining the extent of development of trends in fiscal policy tools and money supply in the narrow sense for three countries...
DOI: 10.33899/iqjoss.v22i2.54077
Ranking of Intuitionistic Fuzzy Numbers by Using Scaling Method
Zryan Brzo Mahmood, Ayad M. Ramadan
Ranking intuitionistic fuzzy numbers (IFN) is a challenging task. Several methods have been presented for ranking IFNs. Also ranking for three IFN is rare. In this work, a new multidimensional...
DOI: 10.33899/iqjoss.v22i2.54078
Integrating Wavelet Shrinkage with SURE and Minimax Thresholding to Enhance Maximum Likelihood Estimation for Gamma-Distributed Data
Hutheyfa Hazem Taha, Taha Hussein Ali, Heyam Hayawi
This paper uses the Maximum Likelihood Estimation method to investigate the impact of data contamination on the accuracy of parameter estimation for the Gamma distribution. A de-noising approach...
DOI: 10.33899/iqjoss.v22i2.54079
A Proposed Method Based on Logistic Regression and Cluster Analysis in Selecting Influential Variables for Kidney Failure Patients
Suhaib Bashar Hameed, Mahmood M Taher
The research aims to study kidney failure by analyzing the relationship between it and a set of independent variables. To achieve this, a method was proposed that relies on reducing the number...
DOI: 10.33899/iqjoss.v22i2.54080
A New Theorem for Lower Bounds in NP-Hard Multi-Objective Scheduling Problems
Hassan A. Mahmood, Ayad M. Ramadan
On a single machine, each of n jobs must be processed continuously. At time zero, every job is ready for processing. The tasks to process a sequence that minimizes the total sum of competition...
DOI: 10.33899/iqjoss.v22i2.54081
Fuzzy Discriminant Analysis with Application
Rafal Talal Saadi , Alla A. Hamoodat
In the current research, two methods of data classification were used, namely; the Linear Discriminant analysis (LDA) and the Fuzzy Discriminant Analysis (FDA). The discriminant analysis is...
DOI: 10.33899/iqjoss.v22i2.54083
Finding the Optimal Prediction of the Occurrence of Earthquakes Using Markov Chains and Artificial Intelligence Methods
Mohammed Qasim Yahya Alawjar
In this research, a method for predicting earthquakes was presented, where seismic data for the Syrian coastal region were studied for the period from 1996 to 2011, which included the earthquake...
DOI: 10.33899/iqjoss.v22i2.54084
Application of Advanced Statistical Models in Big Data Analysis: Modern Methodologies and Techniques
Asmaa S. Qaddoori
This examine investigates the software of advanced statistical fashions in huge records analytics, that specialize in their capability to cope with demanding situations in accuracy, scalability,...
DOI: 10.33899/iqjoss.v22i2.54086
Bayesian Estimation of the Inverse Rayleigh Process under a Non-Homogeneous Poisson Process Framework
Kawar Badie Mahmood
The rationale on which this study is based is that accurate and dependable means to obtain time-dependent failure rates in repairable systems, especially in cases that are not homogeneous, are...
DOI: 10.33899/iqjoss.v22i2.54201
Review Articles
Shrinkage Estimators in Bell Regression Model: Subject Review
Hutheyfa Hazem Taha
Bell regression model has become a very versatile model that replaced the conventional count data models and helps to resolve the problem of over-dispersion where the variance of data points...
DOI: 10.33899/iqjoss.v22i2.54082
Skewness Measures – Article Review
Sarya Mazen Anas, Hyllaa Anas Abdulmjeed
The research aims to define skewness to know the type of skewness, by applying skewness measures such as the Karl-Pearson measure in its cases (median, median and moments) and Kelly’s measure...
DOI: 10.33899/iqjoss.v22i2.54085
