ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

There are many events which causes nonproductive time (NPT) in the drilling industry. The mostly effective in this NPT is pipe sticking event. A considerable amount of time and resources can be spent in efforts to free a stuck pipe. In addition, Unsuccessful fishing operations results in costly alternatives including side-tracking. The drilling in Khabaz oil field poses many operational challenges among of them stuck pipe , lost circulation, flow of salt water during drilling, and hole caving. Stuck pipe can be considered the quite difficult problem in Khabaz oil field due to associated incidents which lead to NPT activities.
Well Khabaz -34 was selected to study the problem of stuck pipe in this field. An analysis of stuck pipe event

There are many events which causes nonproductive time (NPT) in the drilling industry. The mostly effective in this NPT is pipe sticking event. A considerable amount of time and resources can be spent in efforts to free a stuck pipe. In addition, Unsuccessful fishing operations results in costly alternatives including side-tracking. The drilling in Khabaz oil field poses many operational challenges among of them stuck pipe , lost circulation, flow of salt water during drilling, and hole caving. Stuck pipe can be considered the quite difficult problem in Khabaz oil field due to associated incidents which lead to NPT activities.Well Khabaz -34 was selected to study the problem of stuck pipe in this field. An analysis of stuck pipe even

This 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.

        Artificial 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

<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

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

Background: Hypertension is probably the most important public health problem around the world. People with periodontal disease may be at greater risk of hypertension. The inflammatory effects of periodontal disease help to promote endothelial dysfunction in arteries which may lead to changes in blood pressure. Salivary MMP-8 has been associated with both periodontal disease and prevalent hypertension. Aim of study: This study was conducted to measure salivary matrix metalloproteinase - 8, in relation to periodontal health condition among a group of patients with hypertension in comparison with control group. Materials and methods: Ninety subjects, aged 45-50 years old were included in this study, seeking treatment for chest pain in Ibn-A

To obtain the approximate solution to Riccati matrix differential equations, a new variational iteration approach was ‎proposed, which is suggested to improve the accuracy and increase the convergence rate of the approximate solutons to the ‎exact solution. This technique was found to give very accurate results in a few number of iterations. In this paper, the ‎modified approaches were derived to give modified solutions of proposed and used and the convergence analysis to the exact ‎solution of the derived sequence of approximate solutions is also stated and proved. Two examples were also solved, which ‎shows the reliability and applicability of the proposed approach. ‎