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

This paper is concerned with finding solutions to free-boundary inverse coefficient problems. Mathematically, we handle a one-dimensional non-homogeneous heat equation subject to initial and boundary conditions as well as non-localized integral observations of zeroth and first-order heat momentum. The direct problem is solved for the temperature distribution and the non-localized integral measurements using the Crank–Nicolson finite difference method. The inverse problem is solved by simultaneously finding the temperature distribution, the time-dependent free-boundary function indicating the location of the moving interface, and the time-wise thermal diffusivity or advection velocities. We reformulate the inverse problem as a non-

Samples prepared by using carbon black as a filler material and phenolic resin as a binder. The samples were pressed in a (3) cm diameter cylindrical die to (250)MPa and treated thermally within temperature range of (600-1000)oC for two and three hours. Physical properties tests were performed, like density, porosity, and X-ray tests. Moreover vicker microhardness and electric resistivity tests were done. From the results, it can be concluded that density was increased while porosity was decreased gradually with increasing temperature and treating time. In microhardness test, it found that more temperature and treating time cause more hardness. Finally the resistivity was decreased in steps with temperature and treating time. It can be c

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 aim of this research is to recognize the tasks undertaken by   the   headmasters   of   intermediate   schools   concerning   time- administration,   in   accordance   to   the   viewpoints   of   the headmasters   of   intermediate   schools   in   the   Administration   of Education   of   Al-Karkh   the   Third.   The   sample   of   this   research consists   of   (60)   headmasters   and &n

Objective: The present study investigates whether the exposure to low-power diode laser induces denaturation in red blood cell (RBC) membrane protein composition, and determines the irradiation time for when denaturation of membrane protein process begins. Background: A low-energy laser has been used extensively in medical applications. Several studies indicated significant positive effects of laser therapy on biological systems. In contrast, other studies reported that laser induced unwanted changes in cell structure and biological systems. The present work studied the effect of irradiation time of low-power diode laser on the structure of membrane proteins of human RBCs. Materials and methods: The RBC suspension was divided into five equa

The monthly time series of the Total Suspended Solids (TSS) concentrations in Euphrates River at Nasria was analyzed as a time series. The data used for the analysis was the monthly series during (1977-2000).

The series was tested for nonhomogenity and found to be nonhomogeneous. A significant positive jump was observed after 1988. This nonhomogenity was removed using a method suggested by Yevichevich (7). The homogeneous series was then normalized using Box and Cox (2) transformation. The periodic component of the series was fitted using harmonic analyses, and removed from the series to obtain the dependent stochastic component. This component was then modeled using first order autoregressive model (Markovian chain). The above a