The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h

The Purpose of this research is a comparison between two types of multivariate GARCH models BEKK and DVECH to forecast using financial time series which are the series of daily Iraqi dinar exchange rate with dollar, the global daily of Oil price with dollar and the global daily of gold price with dollar for the period from 01/01/2014 till 01/01/2016.The estimation, testing and forecasting process has been computed through the program RATS. Three time series have been transferred to the three asset returns to get the Stationarity, some tests were conducted including Ljung- Box, Multivariate Q and Multivariate ARCH to Returns Series and Residuals Series for both models with comparison between the estimation and for

Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application

In current research Copper was employed for preparing a ternary system of Al–Si alloy in different (0.2–2.5 wt. %) the best was taken is (1.5%wt) of copper that circumstances of solidification for improving the mechanical performance of the available in aluminium alloy. Cast iron molds were prepared to obtain tensile strength testing specimens. Alloys were prepared by employing gas furnaces. The molten metal was poured into a preheated cast-iron mold. The obtained alloy structures were studied using an X-ray diffractometer and optical microscopy. The mechanical performance of the prepared alloys was examined under the influence of different hardening conditions in both heat and non-heat-treated conditions. The outcomes showed at the

The growing demand for sustainable and environmentally friendly alternatives in road construction has led to the exploration of bio-based materials for bitumen modification. This study investigates the use of sugarcane molasses (SM) as a partial replacement of bitumen, evaluating its performance through an interlaboratory study conducted in India and Iraq. Bio-bitumen binders were prepared by partially replacing 30% of conventional bitumen with sugarcane molasses, and their chemical and thermal behaviour was studied. Additionally, laboratory tests were conducted on bio-bitumen mixtures, evaluating rutting resistance, cracking resistance, moisture susceptibility, and stiffness characteristics. A mechanistic-empirical pavement analysis using