A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited grids and used in the training and testing of the used network. A comparison between the calculated and observed cumulative oil production has been carried out through the testing steps of the constructed ANN, an absolute average percentage error of the used network was reached to 4.044%, and this is consider to be an acceptable limit within engineering applications, in addition to that, a good behavior was reached with (FFNNW) and suitable re-entry wells location were identified according to the reservoir configuration (pressure and saturation distribution) output from SRF simulation model at the end of 2005.
The follower to study the markets in the Islamic Mashreq (Iraq, Persia and the country of Ma
Behind the river for the period from the reign of the Prophet Muhammad until the end of the Islamic era) to find that there
A remarkable development in the pattern, shape, planning and privatization of markets
Islamic cities and places are the main conditions for their existence, which is the mosque of the mosque
And markets, and these markets have evolved from being a space in which there are no building and no ceilings to shade them in
The places of sale and purchase to specialized markets classified according to the materials and goods produced in them
This would facilitate the task of supervising it by the market factor and
Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer
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The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained
Fever is a common illness in the pediatric age group ,the causes could be viral ,bacterial and fungal , this study was focused on bacterial pathogens as gram positive like Staphylococci, coagulase positive or negative ,Streptococci and gram negative like E-coli , Klebsialla ,Proteus, Pseudomonas, Burkhoderia , Acinetobacter and others like Pusturella ,E-alkalescendiaper, Haemophillus influenza and yeast like candida . Four thousand and seventy eight blood samples (4078)were collected in a period between January 2011 and the end of May 2012 at the child welfare hospital ,all the samples were cultured on suitable culture media and then biochemical tests were done using API-E 20 and sugar fermentation tests ,sensitivity
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The present study is considered a pioneer investigation that deal with the terrestrial brown garden snail Cornu aspersum (Müller), in Iraq. Cornu aspersum however is considered an exotic species in many parts of the world ,The species is most probably infiltrates with plants transferred from one place to another. The species has gained importance in many ways. Nutritionally, the species is consumed as food item in many countries, but in other cases it is considered as pest for the damage it causes when feeding on valuable plant shoots. It also has medical importance for its role and ability in healing wounds, burns and remedy of other skin problems. This snail species however may act as a vector for some parasitic nematodes that
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تعد الملابس وسيلة هامة لكل مايقوم به الانسان في حياته العامة ، فهي الانطباع والكلمة الخارجية عن ذاته الداخلية فهي تعكس فكرة الفرد عن ذاته وعن شخصيته , كما تعد وسيلة تعبير جمالية وفنية , فهي تساعد على اخفاء عيوب الجسد وابراز محاسنه . ويتوقف اختيار الفرد لملابسه على مجموعة عوامل منها احتياجه , قدراته المالية , سنه , مركزه الاجتماعي , طبيعة عمله ,الظروف الجوية التي يعيش فيها وعلى مايُؤمن به من قيم و
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