Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability. Trend test was performed to ensure that the developed model would follow the physical laws. Results show that the developed model outperforms the published correlations in term of absolute average percent relative error of 6.5%, and correlation coefficient of 96%.
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Wireless sensor networks (WSNs) are emerging in various application like military, area monitoring, health monitoring, industry monitoring and many more. The challenges of the successful WSN application are the energy consumption problem. since the small, portable batteries integrated into the sensor chips cannot be re-charged easily from an economical point of view. This work focusses on prolonging the network lifetime of WSNs by reducing and balancing energy consumption during routing process from hop number point of view. In this paper, performance simulation was done between two types of protocols LEACH that uses single hop path and MODLEACH that uses multi hop path by using Intel Care i3 CPU (2.13GHz) laptop with MATLAB (R2014a). Th
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
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This research involves the application of spectral indices and GIS techniques coupled with the Analytic Hierarchy Process, to assess Baglia site, eastern Missan, as a water harvesting potential site. The AHP and pairwise comparison have been used through select four criteria including TWI, TRI, MNDWI, and NDSI, which were deemed as impact factors for this study. All these criteria have been weighted according to their significance in the water harvesting system. The findings of the AHP analysis method explained that the WH potential zones in Baglia site were divided into three zones, namely, high, medium, and low suitability. The findings demonstrate that Bglia site, where the highly appropriate zone is located in the deep v
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In this paper, a fixed point theorem of nonexpansive mapping is established to study the existence and sufficient conditions for the controllability of nonlinear fractional control systems in reflexive Banach spaces. The result so obtained have been modified and developed in arbitrary space having Opial’s condition by using fixed point theorem deals with nonexpansive mapping defined on a set has normal structure. An application is provided to show the effectiveness of the obtained result.
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This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being
... Show MoreAutorías: Nuha Mohsin Dhahi, Ahmed Thare Hani, Muwafaq Obayes Khudhair. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.
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The monetary policy is a vital method used in implementing monetary stability through: the management of income and adjustment of the price (monetary targets) in order to promote stability and growth of real output (non-cash goals); the tool of interest rate and direct investment guides or movement towards the desired destination; and supervisory instruments of monetary policy in both quantitative and qualitative. The latter is very important as a standard compass to investigate the purposes of the movement monetary policy in the economy. The public and businesses were given monetary policy signals by those tools. In fiscal policy, there are specific techniques to follow to do the spending and collection of revenue. This is done in order to
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This research aims to identify and measure the role of TQM in the process of developing the financial performance of Diyala State Company and show the reality and obstacles, after applying the company's management to the requirements of ISO 9001: 2008 and compare it with its performance before applying this standard, The researcher measured the financial performance by conducting financial analysis of the financial statements and conducting a number of interviews at the company's headquarters, Diyala State Company (one of the Iraqi Ministry of Industry and Minerals formations) was sele
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