. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

     The objective of this research is to measure the training programs and identify the nature and then measure how it reflected on the quality of municipal services provided by the municipal departments investigated by measuring the quality of services based on quality standards, the researcher chose four municipal departments in the Rusafa / Baghdad (164 people) representing the directors and their assistants, officials of the municipal departments, the people and the engineering staff in charge of the task forces as well, including the survey of the views of the concerned persons in the management of the Vocational Training Institute in the Secretariat of the Republic, The quality of the municipal services

The current study aims to test the impact of green training and development on sustainable performance and explore its effects within and outside the Iraqi Ministry of Environment. The main research problem revolves around the question of the extent of implementing green training and development and sustainable performance in the ministry (What is the nature of the relationship between green training and development and sustainable performance in the ministry?). To clarify the relationship between the research variables, two main hypotheses were formulated along with sub-hypotheses. The study also aims to assess the level of the ministry's interest in the research variables and provide key recommendations to enhance sustainable performan

The main purpose of the research is to diagnose the importance of the role that strategic memory plays with its three variables (content, structure, and processes) in helping the human resource department to use the COSO model with its five components (culture and governance, strategy and objectives, performance, communications and information, and feedback) in auditing activities and tasks Her own. As the research problem emphasized the existence of a lack of cognitive perception, of the importance of strategic memory, and the investment of its components in the rationalization of the application of the COSO model. and therefore it can be emphasized that the importance of the research is to provide treatments for problems relate

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial