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 hybrid models in the prediction process when conducting simulation for different sample sizes and when applied to the daily crude oil price time series data, were more efficient than the single models, and the comparison between the single models and the proposed hybrid models was made by comparison scale, mean square error (MSE), and the results showed that the proposed hybrid models have the ability to predict crude oil prices, as they gave more accurate and efficient results.
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This study refers to the development and characterization of silver oxide nanoparticles obtained by X-ray diffraction, nanostructured silver oxide was used in order to calculate the micro strain and crystal size by Halder-Wagner method and by relying on X-ray diffraction diagram of the nonstructural silver oxide, where the results of the crystal size and the micro-strain were 4nm and 0.33 respectively. Other analysis techniques, such as the Size-strain plot, The X-ray diffraction study confirmed that the crystalline nature of silver oxide nanoparticles has a cubic structure. Through the X-ray diffraction results, the crystal size was calculated using Debye-Scherrer and Williamson-Hall methods. Halder-Wagner (HW), Size-strain plot, D
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74 fanners were randomily selected from the Lc:ital. of 406 fanners using the Modern Irrigation System up to November , 2000 , for the purpose of wide adoptation of such system. Rcsults indicated according to the data which has been obtained and statistically analysed by the statistical package for the Social Sciences (SPSS) program showed that the majority of the farmers adopted this new system of irrigation due to the increase in the yield up to 5" .
The synthesis of new substituted cobalt Phthalocyanine (CoPc) was carried out using starting materials Naphthalene-1,4,5, tetracarbonic acid dianhydride (NDI) employing dry process method. Metal oxides (MO) alloy of (60%Ni3O4 40%-Co3O4 ) have been functionalized with multiwall carbon nanotubes (F-MWCNTs) to produce (F-MWCNTs/MO) nanocomposite (E2) and mixed with CoPc to yield (F-MWCNT/CoPc/MO) (E3). These composites were investigated using different analytical and spectrophotometric methods such as 1H-NMR (0-18 ppm), FTIR spectroscopy in the range of (400-4000cm-1), powder X-rays diffraction (PXRD, 2θ o = 10-80), Raman spectroscopy (0-4000 cm-1), and UV-Visib
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his project try to explain the using ability of spatial techniques for land cover change detection on regional level with the time parameter and did select for explain these abilities study case (Hewaizah marsh ) . this area apply to many big changes with the time. These changes made action on characters and behaviors of this area as well as all activities in it . This Project concerting to recognize the Using importance of remote sensing and GIS Methodology in data collecting for the changes of land use and the methodology for the analyses and getting the results for the next using as a base data for development and drawing the plans as well as in regional planning .This project focus on practical
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PVC membrane sensor for the selective determination of Mefenamic acid (MFA) was constructed. The sensor is based on ion association of MFA with Dodecaphospho molybdic acid (PMA) and Dodeca–Tungstophosphoric acid(PTA) as ion pairs. Nitro benzene (NB) and di-butyl phthalate (DBPH) were used as plasticizing agents in PVC matrix membranes. The specification of sensor based on PMA showed a linear response of a concentration range 1.0 × 10–2 –1.0 × 10–5 M, Nernstian slopes of 17.1-18.86 mV/ decade, detection limit of 7 × 10-5 -9.5 × 10 -7M, pH range 3 – 8 , with correlation coefficients lying between 0.9992 and 0.9976, respectively. By using the ionphore based on PTA gives a concentration range of 1.0 × 10–4 –1.0 × 10–5 M,
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Experience the Islamic financial industry faces many challenges, most notably the lack of proper risk management tools that meet the requirements of legality and economic efficiency advantage from another side, so it requires the search for innovative ways to manage the risk of Islamic banking, Islamic finance industry is manufacture up-to-date, if compared with the financial industry (traditional), which increases the problematic of risk management in the Islamic financial industry nature of treatment which should be compatible with Islamic law, as well as economic efficiency, thereby Progress came the importance of research to highlight the entrance to Islamic financial engineering and the goals sought to be achieved through the use of
... Show MoreThis article presents and explores the theoretical aspect in the use of Arab Islamic theme by the western writers to obtain and achieve individual motives. In this study the model for the theory of Arab presence in Andalusia , through the book entitled “ Alhamra” by the English writer Washington Erving ,was analyzed.
The most important results in this research: the success of the author in the employment of the Islamic history in the formation of the first American legend, Columbus legend, through the selection of the right thoughts to establish his American National theory. The author compared between the Andalusia experience and the Arab occupation to Spain and the American conquest of the new
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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