The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

The research aimed to test the effect of independent variables career plateaus and workaholism on employees loyalty through the influence of the mediator variable organizational socialization. Descriptive approach with survey style   on a sample of managers and executives in the Iraqi Drilling Company in Basra's (123) employees. The most important findings of the research are: the existence of a significant effect of the independent variables career plateaus and workaholism in employees loyalty by having a mediator variable organizational socialization and introduced numerical from recommendations.                    &nbs

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

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

. 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

في مدينة الري القريبة من طهران الحالية ولد ابو بكر محمد بن يحيى بن زكريا الرازي سنة 251هـ/865 م وسميً بالرازي نسبة الى مدينة الري 0 أحب الرازي الغناء والضرب على العود في بداية حياته ثم هجر ذلك كله واتجه الى الطب والكيمياء 0 درس الطب في شبابه في بغداد وقد اخطأ بعض المؤرخين في ظنهم ان

God bestowed upon the Imams of the Ahl al-Bayt (peace be upon them) knowledge and wisdom, in addition to give them virtue as long as it was not given to anyone from the worlds. knowledge have been enriched from them that cause pride.

This research deals with the ideas of Imam Muhammad bin Al-Waleed bin Khalaf bin Sulaiman bin Ayyub , Al -Qurashi, The Moroccan, The  Andalusian, Al-Maliki. He was  known as Abu Bakr Al-Tartoushey , where thesis deals  with the details of his personal life and as well as his scientific path  as well as  his works, and also covered the views of jurisprudence in the personal status and especially on the subject of divorce and inheritance,