The relationship between government revenues and the fiscal balance represents a central pillar in the analysis of fiscal sustainability. However, its modeling faces a fundamental challenge in the form of structural uncertainty, which is not captured by point estimates in traditional models such as ARDL, as these models assume structural stability that is inconsistent with the nature of rentier economies. The current study aims to develop a fuzzy framework by constructing a Fuzzy Autoregressive Distributed Lag (FARDL) model. This is achieved through integrating the Autoregressive Distributed Lag (ARDL) approach with fuzzy logic theory, thereby enabling the incorporation of uncertainty into the inherent structure of the economic relationship rather than confining it to the stochastic error term. The fuzzy parameters are estimated using a Quadratic Programming (QP) algorithm, and the proposed model is empirically applied to quarterly data for the Iraqi economy over the period (2013-2025). The results provide evidence of a long-run equilibrium relationship between government revenues and the fiscal balance, alongside a persistent structural tendency toward fiscal deficits. Government revenues are shown to have a positive impact on the fiscal balance, however, this impact is uncertain due to revenue uncertainty and resource efficiency. The results of stability tests reveal the dynamic stability of the model, suggesting the existence of a self-equilibrating mechanism. Additionally, the difference between the ARDL and FARDL models shows a descriptive superiority of the fuzzy model in terms of forecasting performance (in-sample and out-sample) with statistically equivalent predictive efficiency. At the same time, the FARDL model offers a more flexible representation with the possibility of interval estimates and multiple scenarios, thus improving the analysis of fiscal sustainability under structural uncertainty.
The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.
In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.
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... Show MoreIn this study, different methods were used for estimating location parameter and scale parameter for extreme value distribution, such as maximum likelihood estimation (MLE) , method of moment estimation (ME),and approximation estimators based on percentiles which is called white method in estimation, as the extreme value distribution is one of exponential distributions. Least squares estimation (OLS) was used, weighted least squares estimation (WLS), ridge regression estimation (Rig), and adjusted ridge regression estimation (ARig) were used. Two parameters for expected value to the percentile as estimation for distribution f
... Show MoreThe research problem boils question is there in Riyadh organizational climate that enables them to do their work properly and whether there are differences between the government and private Riyadh depending on the organizational climate has sought Find measure: 1 regulatory climate for kindergarten 2. The difference between government and private Riyadh depending on the organizational climate. Limited research on the (200) parameter of the Riyadh government and private parameters for the year (20,142,015) In order to achieve the research objectives the researchers built a regulatory climate in accordance with the scientific steps to build a psychological scales measure After the formulation of climate regulation paragraphs of the (30) p
... Show MoreBreast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o
... Show MoreA Spectroscopic study has been focused in this article to study one of the main types of active galaxies which are quasars, and to be more precise this research focuses on studying the correlation between the main engine of Quasi-Stellar Objects (QSO), the central black hole mass (SMBH) and other physical properties (e.g. the star formation rate (SFR)). Twelve objects have been randomly selected for “The Half Million Quasars (HMQ) Catalogue” published in 2015 and the data collected from Salon Digital Sky survey (SDSS) Dr. 16. The redshift range of these galaxies were between (0.05 – 0.17). The results show a clear linear proportionality between the SMBH and the SFR, as well as direct proportional between the luminosit
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This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.
The comparison was done by simulation using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood with sample size (n = 30) is the best to represent the maternal mortality data after it has been reliance value param
... Show MoreThe aim of the research is to explain the nature of the relationship between the dimensions of the strategic recovery of the service represented by (compensation, speed of response, apology, initiative (defining the problem) and the strategic goals of the company represented in (profitability, growth, community service, employee satisfaction) in the National Insurance Company, it has been approved The questionnaire as a tool to collect data and information from the sample of (58) who are in (department manager, M. department director, division official, unit official) and the statistical program (spss) was used in calculating (arithmetic mean, standard deviation, coefficient of variation, coefficient of Correlation, t-test, varia
... Show MoreIn this paper, we describe the cases of marriage and divorce in the city of Baghdad on both sides of Rusafa and Karkh, we collected the data in this research from the Supreme Judicial Council and used the cubic spline interpolation method to estimate the function that passing through given points as well as the extrapolation method which was applied for estimating the cases of marriage and divorce for the next year and comparison between Rusafa and Karkh by using the MATLAB program.
Physical measurements are one of the basic factors that affect the performance of the goalkeeper, especially when confronting fixed kicks that require special skills such as the reaction and accuracy in concentration, and with technological development artificial intelligence has become an effective tool for analyzing mathematical data that is difficult to discover in traditional methods The study aims to employ techniques Artificial intelligence to study the relationship between physical measurements and the accuracy of confronting the fixed kicks of goalkeepers in football. This study will contribute to providing a deeper understanding of physical factors that affect the performance of goalkeepers, in addition to designing dedicat
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