The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.
This study examined the tagged (the matter, its ruling, and examples of its applications in Ahmadiyya interpretations), the study of devising formulas of commissioning, especially the matter from the book of interpretation, which is: (Ahmadiyyeh’s interpretations), and the contemplative of the nature of (Ahmadiyya’s interpretations) realizes that the cognitive, linguistic and juristic knowledge product and the verses of judgments And other is the focus of this immortal travel, as it is truly a comprehensive book containing what the students of knowledge, scholars and the general public need in terms of interpreting the legal verses, and it is not possible to reach an understanding of the Book of God Almighty, and to clarify his purpo
... Show MoreThe magnetic properties of a pure Nickel metal and Nickel-Zinc-Manganese ferrites having the chemical formula Ni0.1(Zn0.4Mn0.6)0.9Fe2O4 were studied. The phase formation and crystal structure was studied by using x-ray diffraction which confirmed the formation of pure single spinel cubic phase with space group (Fd3m) in the ferrite. The samples microstructure was studied with scanning electron microstructure and EDX. The magnetic properties of the ferrite and nickel metal were characterized by using a laboratory setup with a magnetic field in the range from 0-500 G. The ferrite showed perfect soft spinel phase behavior while the nickel sample showed higher magnetic loss an
... Show MoreBackground: Pressure ulcers remain a serious complication for immobile patients and a burden for healthcare professionals. Objectives: To assess health behavior prevention among critical care nurses regarding pressure ulcer prevention for hospitalized patients and to find out the relationship between critical care nurses health behavior prevention and sociodemographic variables. Methods: A cross-sectional design study was carried out in critical care units at three teaching hospitals. The study period extended from November 1, 2022, to January 28, 2023. Non-probability purposive sampling, whose target population was 100 nurses who work in critical care units in Baghdad, Iraq. The data were collected using a self-administered questio
... Show MoreIn many organizations, employees who have high mental skills are the main source of organizational creativity. When a firm does not put creativity as a goal, cannot stand solid against the competition. Nowadays, knowledge is the path to discover the innovation and creativity aspects, This can assist the firm to stand face to face with competition in the market. The importance of this research comes from detecting and knowing the relation between creativity and knowledge to know and detect the influence of organizational creativity on backing the management of knowledge and determine the final results. The problem of research is to trace the role of organizational creativity on knowledge management processes in order to enable the
... Show MoreArtificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and
... Show MoreThis work aims to analyze a three-dimensional discrete-time biological system, a prey-predator model with a constant harvesting amount. The stage structure lies in the predator species. This analysis is done by finding all possible equilibria and investigating their stability. In order to get an optimal harvesting strategy, we suppose that harvesting is to be a non-constant rate. Finally, numerical simulations are given to confirm the outcome of mathematical analysis.
Simulation experiments are a means of solving in many fields, and it is the process of designing a model of the real system in order to follow it and identify its behavior through certain models and formulas written according to a repeating software style with a number of iterations. The aim of this study is to build a model that deals with the behavior suffering from the state of (heteroskedasticity) by studying the models (APGARCH & NAGARCH) using (Gaussian) and (Non-Gaussian) distributions for different sample sizes (500,1000,1500,2000) through the stage of time series analysis (identification , estimation, diagnostic checking and prediction). The data was generated using the estimations of the parameters resulting f
... Show More<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c
... Show More