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jeasiq-1169
Comparison of repetitive estimation methodsSelf-data
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In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation)  structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of  these procedures and compare them using generated data.

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Publication Date
Thu Jan 01 2026
Journal Name
Aip Conference Proceedings
Estimation parameter for non-linear regression by using HGSABAT algorithm
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This study offers a new Mixed Meta Heuristics algorithm (HGSABAT) for estimating the parameter values of each of the six categories of Non-Linear regression models examined (Misrald, Meyer4, Meyer7, Militky4, Militky2, and MGH09) by combining the Gravitational Search Algorithm and Bat Algorithm. Some models have different numbers of parameters. For example, the Misrald and Militky2 models of the Non-Linear Regression model have two parameters (Bl, B2). In contrast, the MGH09 and Militky4 models have four parameters (MGHl, MGH2, MGH3, and MGH4), in which location as the Meyer4 and Meyer7 models have three attributes (Meyerl, MGH2, and MGH3). To examine the effectiveness of the suggested Hybrid Meta Heuristics algorithm (HGSABAT), a simulatio

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Survival estimation for singly type one censored sample based on generalized Rayleigh distribution
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This paper interest to estimation the unknown parameters for generalized Rayleigh distribution model based on censored samples of singly type one . In this paper the probability density function for generalized Rayleigh is defined with its properties . The maximum likelihood estimator method is used to derive the point estimation for all unknown parameters based on iterative method , as Newton – Raphson method , then derive confidence interval estimation which based on Fisher information matrix . Finally , testing whether the current model ( GRD ) fits to a set of real data , then compute the survival function and hazard function for this real data.

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Publication Date
Sat Mar 26 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role of Big Data applications in forecasting corporate bankruptcy: Field analysis in the Saudi Business Environment
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This study aimed to investigate the role of Big Data in forecasting corporate bankruptcy and that is through a field analysis in the Saudi business environment, to test that relationship. The study found: that Big Data is a recently used variable in the business context and has multiple accounting effects and benefits. Among the benefits is forecasting and disclosing corporate financial failures and bankruptcies, which is based on three main elements for reporting and disclosing that, these elements are the firms’ internal control system, the external auditing, and financial analysts' forecasts. The study recommends: Since the greatest risk of Big Data is the slow adaptation of accountants and auditors to these technologies, wh

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Publication Date
Sun Jun 01 2014
Journal Name
International Journal Of Inventive Engineering And Science,
Increase the Capacity Amount of Data Hiding to Least Significant BIT Method
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Investigating the quality of open street map roads data inside Baghdad city
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Publication Date
Tue Nov 10 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Hybridization Methodology of ARMA-FIGARCH Model to Examine Gasoline Data in Iraq
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Publication Date
Sun Apr 01 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Hiding Data in Color Image Using Least Significant Bits of Blue Sector
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Publication Date
Thu Feb 01 2018
Journal Name
Applied Mathematical Modelling
Identification of a multi-dimensional space-dependent heat source from boundary data
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Publication Date
Fri Jan 01 2010
Journal Name
Ibn Al- Haitham J. Fo R Pure & Appl. Sci
Evaluation of The Nuclear Data on(α,n)Reaction for Natural Molybdenum
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The cross section evaluation for (α,n) reaction was calculated according to the available International Atomic Energy Agency (IAEA) and other experimental published data . These cross section are the most recent data , while the well known international libraries like ENDF , JENDL , JEFF , etc. We considered an energy range from threshold to 25 M eV in interval (1 MeV). The average weighted cross sections for all available experimental and theoretical(JENDL) data and for all the considered isotopes was calculated . The cross section of the element is then calculated according to the cross sections of the isotopes of that element taking into account their abundance . A mathematical representative equation for each of the element

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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