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.
In the geotechnical and terramechanical engineering applications, precise understandings are yet to be established on the off-road structures interacting with complex soil profiles. Several theoretical and experimental approaches have been used to measure the ultimate bearing capacity of the layered soil, but with a significant level of differences depending on the failure mechanisms assumed. Furthermore, local displacement fields in layered soils are not yet studied well. Here, the bearing capacity of a dense sand layer overlying loose sand beneath a rigid beam is studied under the plain-strain condition. The study employs using digital particle image velocimetry (DPIV) and finite element method (FEM) simulations. In the FEM, an experiment
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Background: Anaemia is a major public health concern and is one of the most prevalent health issue in women within reproductive age group.
Objective: to assess maternal knowledge related to anaemia during pregnancy.
Type of the study: A cross –sectional study.
Method: The study including 200 mothers who attended selected primary health care centres, Baghdad during November and December 2015, they completed a previously prepared questionnaire coveringsocio-demographic characteristics and knowledge regarding anaemia in 4 main domains. The responses were analysed by using frequency, percentage and percent score for each statement a
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Authors in this work design efficient neural networks, which are based on the modified Levenberg - Marquardt (LM) training algorithms to solve non-linear fourth - order three -dimensional partial differential equations in the two kinds in the periodic and in the non-periodic - Periodic. Software reliability growth models are essential tools for monitoring and evaluating the evolution of software reliability. Software defect detection events that occur during testing and operation are often treated as counting processes in many current models. However, when working with large software systems, the error detection process should be viewed as a random process with a continuous state space, since the number of faults found during testin
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نحو تعزيز المشاركة السياسية للطالبات الجامعيات الفلسطينيات
Dialysis is a stressful process and follows various psychological and social problems, which can lead to psychological disturbances. Patients on dialysis experience psychological distress, and the reduction of stress in patients provides psychological resources to cope with their physical condition. The study aimed to evaluate the effect of deep-breathing exercise training on the level of stress among maintenance hemodialysis patients.
This study is a randomized
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